Overview

Brought to you by YData

Dataset statistics

Number of variables223
Number of observations601451
Missing cells91002889
Missing cells (%)67.9%
Total size in memory1011.2 MiB
Average record size in memory1.7 KiB

Variable types

Numeric23
Unsupported123
Text73
Boolean4

Dataset

DescriptionMammal NMNH Extant Specimen Records 0054884-241126133413365
URLhttps://doi.org/10.15468/dl.dys66y

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
collectionID has constant value "urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22" Constant
collectionCode has constant value "MAMM" Constant
datasetName has constant value "NMNH Extant Biology" Constant
occurrenceStatus has constant value "PRESENT" Constant
kingdom has constant value "Animalia" Constant
datasetKey has constant value "821cc27a-e3bb-4bc5-ac34-89ada245069d" Constant
publishingCountry has constant value "US" Constant
kingdomKey has constant value "1" Constant
protocol has constant value "EML" Constant
lastCrawled has constant value "2024-12-02T11:48:23.416Z" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
hasGeospatialIssues is highly imbalanced (96.7%) Imbalance
isSequenced is highly imbalanced (98.1%) Imbalance
accessRights has 601451 (100.0%) missing values Missing
bibliographicCitation has 601451 (100.0%) missing values Missing
language has 601451 (100.0%) missing values Missing
references has 601451 (100.0%) missing values Missing
rightsHolder has 601451 (100.0%) missing values Missing
type has 601451 (100.0%) missing values Missing
datasetID has 601451 (100.0%) missing values Missing
ownerInstitutionCode has 601451 (100.0%) missing values Missing
informationWithheld has 601451 (100.0%) missing values Missing
dataGeneralizations has 601451 (100.0%) missing values Missing
dynamicProperties has 601451 (100.0%) missing values Missing
recordNumber has 50821 (8.4%) missing values Missing
recordedBy has 55563 (9.2%) missing values Missing
recordedByID has 601451 (100.0%) missing values Missing
organismQuantity has 601451 (100.0%) missing values Missing
organismQuantityType has 601451 (100.0%) missing values Missing
sex has 88216 (14.7%) missing values Missing
lifeStage has 550088 (91.5%) missing values Missing
reproductiveCondition has 601451 (100.0%) missing values Missing
caste has 601451 (100.0%) missing values Missing
behavior has 601451 (100.0%) missing values Missing
vitality has 601451 (100.0%) missing values Missing
establishmentMeans has 601451 (100.0%) missing values Missing
degreeOfEstablishment has 601451 (100.0%) missing values Missing
pathway has 601451 (100.0%) missing values Missing
georeferenceVerificationStatus has 601451 (100.0%) missing values Missing
preparations has 26965 (4.5%) missing values Missing
disposition has 601451 (100.0%) missing values Missing
associatedOccurrences has 601451 (100.0%) missing values Missing
associatedReferences has 601451 (100.0%) missing values Missing
associatedSequences has 600397 (99.8%) missing values Missing
associatedTaxa has 601451 (100.0%) missing values Missing
otherCatalogNumbers has 601451 (100.0%) missing values Missing
occurrenceRemarks has 590662 (98.2%) missing values Missing
organismID has 601451 (100.0%) missing values Missing
organismName has 601451 (100.0%) missing values Missing
organismScope has 601451 (100.0%) missing values Missing
associatedOrganisms has 601451 (100.0%) missing values Missing
previousIdentifications has 601451 (100.0%) missing values Missing
organismRemarks has 601451 (100.0%) missing values Missing
materialEntityID has 601451 (100.0%) missing values Missing
materialEntityRemarks has 601451 (100.0%) missing values Missing
verbatimLabel has 601451 (100.0%) missing values Missing
materialSampleID has 601451 (100.0%) missing values Missing
eventID has 601451 (100.0%) missing values Missing
parentEventID has 601451 (100.0%) missing values Missing
eventType has 601451 (100.0%) missing values Missing
fieldNumber has 601451 (100.0%) missing values Missing
eventDate has 28480 (4.7%) missing values Missing
eventTime has 601451 (100.0%) missing values Missing
startDayOfYear has 67487 (11.2%) missing values Missing
endDayOfYear has 67487 (11.2%) missing values Missing
year has 28519 (4.7%) missing values Missing
month has 45368 (7.5%) missing values Missing
day has 68254 (11.3%) missing values Missing
verbatimEventDate has 36490 (6.1%) missing values Missing
habitat has 468915 (78.0%) missing values Missing
samplingProtocol has 601451 (100.0%) missing values Missing
sampleSizeValue has 601451 (100.0%) missing values Missing
sampleSizeUnit has 601451 (100.0%) missing values Missing
samplingEffort has 601451 (100.0%) missing values Missing
fieldNotes has 601451 (100.0%) missing values Missing
eventRemarks has 601451 (100.0%) missing values Missing
locationID has 601451 (100.0%) missing values Missing
higherGeographyID has 601451 (100.0%) missing values Missing
continent has 39181 (6.5%) missing values Missing
waterBody has 539858 (89.8%) missing values Missing
islandGroup has 596682 (99.2%) missing values Missing
island has 564842 (93.9%) missing values Missing
stateProvince has 93954 (15.6%) missing values Missing
county has 447402 (74.4%) missing values Missing
municipality has 601451 (100.0%) missing values Missing
locality has 35404 (5.9%) missing values Missing
verbatimLocality has 601451 (100.0%) missing values Missing
verbatimElevation has 599861 (99.7%) missing values Missing
verticalDatum has 601451 (100.0%) missing values Missing
verbatimDepth has 601451 (100.0%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 601451 (100.0%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 601451 (100.0%) missing values Missing
locationAccordingTo has 601451 (100.0%) missing values Missing
locationRemarks has 601451 (100.0%) missing values Missing
decimalLatitude has 447917 (74.5%) missing values Missing
decimalLongitude has 447917 (74.5%) missing values Missing
coordinateUncertaintyInMeters has 601451 (100.0%) missing values Missing
coordinatePrecision has 601451 (100.0%) missing values Missing
pointRadiusSpatialFit has 601451 (100.0%) missing values Missing
verbatimCoordinateSystem has 468202 (77.8%) missing values Missing
verbatimSRS has 601451 (100.0%) missing values Missing
footprintWKT has 601451 (100.0%) missing values Missing
footprintSRS has 601451 (100.0%) missing values Missing
footprintSpatialFit has 601451 (100.0%) missing values Missing
georeferencedBy has 601451 (100.0%) missing values Missing
georeferencedDate has 601451 (100.0%) missing values Missing
georeferenceProtocol has 592196 (98.5%) missing values Missing
georeferenceSources has 601451 (100.0%) missing values Missing
georeferenceRemarks has 601383 (> 99.9%) missing values Missing
geologicalContextID has 601451 (100.0%) missing values Missing
earliestEonOrLowestEonothem has 601451 (100.0%) missing values Missing
latestEonOrHighestEonothem has 601451 (100.0%) missing values Missing
earliestEraOrLowestErathem has 601451 (100.0%) missing values Missing
latestEraOrHighestErathem has 601451 (100.0%) missing values Missing
earliestPeriodOrLowestSystem has 601451 (100.0%) missing values Missing
latestPeriodOrHighestSystem has 601451 (100.0%) missing values Missing
earliestEpochOrLowestSeries has 601451 (100.0%) missing values Missing
latestEpochOrHighestSeries has 601451 (100.0%) missing values Missing
earliestAgeOrLowestStage has 601451 (100.0%) missing values Missing
latestAgeOrHighestStage has 601451 (100.0%) missing values Missing
lowestBiostratigraphicZone has 601451 (100.0%) missing values Missing
highestBiostratigraphicZone has 601451 (100.0%) missing values Missing
lithostratigraphicTerms has 601451 (100.0%) missing values Missing
group has 601451 (100.0%) missing values Missing
formation has 601451 (100.0%) missing values Missing
member has 601451 (100.0%) missing values Missing
bed has 601451 (100.0%) missing values Missing
identificationID has 601451 (100.0%) missing values Missing
verbatimIdentification has 601451 (100.0%) missing values Missing
identificationQualifier has 599947 (99.7%) missing values Missing
typeStatus has 597715 (99.4%) missing values Missing
identifiedBy has 593267 (98.6%) missing values Missing
identifiedByID has 601451 (100.0%) missing values Missing
dateIdentified has 601451 (100.0%) missing values Missing
identificationReferences has 601451 (100.0%) missing values Missing
identificationVerificationStatus has 601451 (100.0%) missing values Missing
identificationRemarks has 601451 (100.0%) missing values Missing
taxonID has 601451 (100.0%) missing values Missing
scientificNameID has 601451 (100.0%) missing values Missing
parentNameUsageID has 601451 (100.0%) missing values Missing
originalNameUsageID has 601451 (100.0%) missing values Missing
nameAccordingToID has 601451 (100.0%) missing values Missing
namePublishedInID has 601451 (100.0%) missing values Missing
taxonConceptID has 601451 (100.0%) missing values Missing
acceptedNameUsage has 601451 (100.0%) missing values Missing
parentNameUsage has 601451 (100.0%) missing values Missing
originalNameUsage has 601451 (100.0%) missing values Missing
nameAccordingTo has 601451 (100.0%) missing values Missing
namePublishedIn has 601451 (100.0%) missing values Missing
namePublishedInYear has 601451 (100.0%) missing values Missing
superfamily has 601451 (100.0%) missing values Missing
subfamily has 601451 (100.0%) missing values Missing
tribe has 601451 (100.0%) missing values Missing
subtribe has 601451 (100.0%) missing values Missing
subgenus has 601451 (100.0%) missing values Missing
infragenericEpithet has 601451 (100.0%) missing values Missing
specificEpithet has 29657 (4.9%) missing values Missing
infraspecificEpithet has 386527 (64.3%) missing values Missing
cultivarEpithet has 601451 (100.0%) missing values Missing
verbatimTaxonRank has 601451 (100.0%) missing values Missing
vernacularName has 601451 (100.0%) missing values Missing
nomenclaturalCode has 601451 (100.0%) missing values Missing
nomenclaturalStatus has 601451 (100.0%) missing values Missing
taxonRemarks has 601451 (100.0%) missing values Missing
elevation has 496901 (82.6%) missing values Missing
elevationAccuracy has 597572 (99.4%) missing values Missing
depth has 601448 (> 99.9%) missing values Missing
depthAccuracy has 601451 (100.0%) missing values Missing
distanceFromCentroidInMeters has 601180 (> 99.9%) missing values Missing
mediaType has 45831 (7.6%) missing values Missing
subgenusKey has 601451 (100.0%) missing values Missing
speciesKey has 29663 (4.9%) missing values Missing
species has 29663 (4.9%) missing values Missing
typifiedName has 601451 (100.0%) missing values Missing
relativeOrganismQuantity has 601451 (100.0%) missing values Missing
projectId has 601451 (100.0%) missing values Missing
gbifRegion has 15955 (2.7%) missing values Missing
level0Gid has 473902 (78.8%) missing values Missing
level0Name has 473902 (78.8%) missing values Missing
level1Gid has 473930 (78.8%) missing values Missing
level1Name has 473930 (78.8%) missing values Missing
level2Gid has 475037 (79.0%) missing values Missing
level2Name has 475037 (79.0%) missing values Missing
level3Gid has 539154 (89.6%) missing values Missing
level3Name has 539390 (89.7%) missing values Missing
iucnRedListCategory has 210302 (35.0%) missing values Missing
individualCount is highly skewed (γ1 = 700.9743605) Skewed
phylumKey is highly skewed (γ1 = 548.3830778) Skewed
classKey is highly skewed (γ1 = -548.3826219) Skewed
gbifID has unique values Unique
occurrenceID has unique values Unique
accessRights is an unsupported type, check if it needs cleaning or further analysis Unsupported
bibliographicCitation is an unsupported type, check if it needs cleaning or further analysis Unsupported
language is an unsupported type, check if it needs cleaning or further analysis Unsupported
references is an unsupported type, check if it needs cleaning or further analysis Unsupported
rightsHolder is an unsupported type, check if it needs cleaning or further analysis Unsupported
type is an unsupported type, check if it needs cleaning or further analysis Unsupported
datasetID is an unsupported type, check if it needs cleaning or further analysis Unsupported
ownerInstitutionCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
informationWithheld is an unsupported type, check if it needs cleaning or further analysis Unsupported
dataGeneralizations is an unsupported type, check if it needs cleaning or further analysis Unsupported
dynamicProperties is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantityType is an unsupported type, check if it needs cleaning or further analysis Unsupported
reproductiveCondition is an unsupported type, check if it needs cleaning or further analysis Unsupported
caste is an unsupported type, check if it needs cleaning or further analysis Unsupported
behavior is an unsupported type, check if it needs cleaning or further analysis Unsupported
vitality is an unsupported type, check if it needs cleaning or further analysis Unsupported
establishmentMeans is an unsupported type, check if it needs cleaning or further analysis Unsupported
degreeOfEstablishment is an unsupported type, check if it needs cleaning or further analysis Unsupported
pathway is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
disposition is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOccurrences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedTaxa is an unsupported type, check if it needs cleaning or further analysis Unsupported
otherCatalogNumbers is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismName is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismScope is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOrganisms is an unsupported type, check if it needs cleaning or further analysis Unsupported
previousIdentifications is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityID is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLabel is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialSampleID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentEventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventType is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNumber is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventTime is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingProtocol is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeValue is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeUnit is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingEffort is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNotes is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
higherGeographyID is an unsupported type, check if it needs cleaning or further analysis Unsupported
municipality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLocality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verticalDatum is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimDepth is an unsupported type, check if it needs cleaning or further analysis Unsupported
minimumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
maximumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinateUncertaintyInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinatePrecision is an unsupported type, check if it needs cleaning or further analysis Unsupported
pointRadiusSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintWKT is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedBy is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceSources is an unsupported type, check if it needs cleaning or further analysis Unsupported
geologicalContextID is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEonOrLowestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEonOrHighestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEraOrLowestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEraOrHighestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestPeriodOrLowestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestPeriodOrHighestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEpochOrLowestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEpochOrHighestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestAgeOrLowestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestAgeOrHighestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
lowestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
highestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
lithostratigraphicTerms is an unsupported type, check if it needs cleaning or further analysis Unsupported
group is an unsupported type, check if it needs cleaning or further analysis Unsupported
formation is an unsupported type, check if it needs cleaning or further analysis Unsupported
member is an unsupported type, check if it needs cleaning or further analysis Unsupported
bed is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimIdentification is an unsupported type, check if it needs cleaning or further analysis Unsupported
identifiedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
dateIdentified is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonID is an unsupported type, check if it needs cleaning or further analysis Unsupported
scientificNameID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingToID is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInID is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonConceptID is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedIn is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
superfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
subfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
tribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subtribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenus is an unsupported type, check if it needs cleaning or further analysis Unsupported
infragenericEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
cultivarEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimTaxonRank is an unsupported type, check if it needs cleaning or further analysis Unsupported
vernacularName is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
depthAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenusKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
typifiedName is an unsupported type, check if it needs cleaning or further analysis Unsupported
relativeOrganismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
projectId is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-01-07 15:46:47.039400
Analysis finished2025-01-07 15:47:03.323120
Duration16.28 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Real number (ℝ)

Unique 

Distinct601451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1351494954
Minimum1317202454
Maximum4987327817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:03.358283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1317202454
5-th percentile1317497022
Q11318680166
median1320162909
Q31321648937
95-th percentile1322830206
Maximum4987327817
Range3670125363
Interquartile range (IQR)2968770.5

Descriptive statistics

Standard deviation270770933.6
Coefficient of variation (CV)0.2003492006
Kurtosis92.9269455
Mean1351494954
Median Absolute Deviation (MAD)1484531
Skewness9.608471051
Sum8.128579916 × 1014
Variance7.33168985 × 1016
MonotonicityNot monotonic
2025-01-07T10:47:03.424409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1828975165 1
 
< 0.1%
1322535732 1
 
< 0.1%
1322538146 1
 
< 0.1%
1317206206 1
 
< 0.1%
1317210025 1
 
< 0.1%
1317210456 1
 
< 0.1%
1317211504 1
 
< 0.1%
1676036694 1
 
< 0.1%
4041142496 1
 
< 0.1%
4041103536 1
 
< 0.1%
Other values (601441) 601441
> 99.9%
ValueCountFrequency (%)
1317202454 1
< 0.1%
1317202483 1
< 0.1%
1317202490 1
< 0.1%
1317202494 1
< 0.1%
1317202495 1
< 0.1%
ValueCountFrequency (%)
4987327817 1
< 0.1%
4976689815 1
< 0.1%
4976689796 1
< 0.1%
4976689062 1
< 0.1%
4976688665 1
< 0.1%

accessRights
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

bibliographicCitation
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

language
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:03.467924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4210157
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 601451
100.0%
2025-01-07T10:47:03.565675image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1202902
28.6%
0 1202902
28.6%
_ 1202902
28.6%
1 601451
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1202902
28.6%
0 1202902
28.6%
_ 1202902
28.6%
1 601451
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1202902
28.6%
0 1202902
28.6%
_ 1202902
28.6%
1 601451
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1202902
28.6%
0 1202902
28.6%
_ 1202902
28.6%
1 601451
14.3%
Distinct29672
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:03.696987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters12029020
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12662 ?
Unique (%)2.1%

Sample

1st row2021-08-09T14:50:00Z
2nd row2020-04-09T11:54:00Z
3rd row2020-03-17T10:16:00Z
4th row2020-05-20T10:50:00Z
5th row2017-12-08T15:28:00Z
ValueCountFrequency (%)
2021-01-11t15:15:00z 2641
 
0.4%
2023-02-10t10:31:00z 2632
 
0.4%
2021-08-09t14:46:00z 2522
 
0.4%
2020-07-20t15:30:00z 2313
 
0.4%
2017-12-08t15:27:00z 2105
 
0.3%
2021-08-09t14:49:00z 2096
 
0.3%
2017-12-08t15:33:00z 2050
 
0.3%
2017-12-08t15:36:00z 2008
 
0.3%
2020-07-24t16:11:00z 1979
 
0.3%
2017-12-08t15:35:00z 1972
 
0.3%
Other values (29662) 579133
96.3%
2025-01-07T10:47:03.881176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3217264
26.7%
2 1683114
14.0%
1 1412891
11.7%
- 1202902
 
10.0%
: 1202902
 
10.0%
T 601451
 
5.0%
Z 601451
 
5.0%
4 455860
 
3.8%
3 439973
 
3.7%
5 428273
 
3.6%
Other values (4) 782939
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12029020
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3217264
26.7%
2 1683114
14.0%
1 1412891
11.7%
- 1202902
 
10.0%
: 1202902
 
10.0%
T 601451
 
5.0%
Z 601451
 
5.0%
4 455860
 
3.8%
3 439973
 
3.7%
5 428273
 
3.6%
Other values (4) 782939
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12029020
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3217264
26.7%
2 1683114
14.0%
1 1412891
11.7%
- 1202902
 
10.0%
: 1202902
 
10.0%
T 601451
 
5.0%
Z 601451
 
5.0%
4 455860
 
3.8%
3 439973
 
3.7%
5 428273
 
3.6%
Other values (4) 782939
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12029020
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3217264
26.7%
2 1683114
14.0%
1 1412891
11.7%
- 1202902
 
10.0%
: 1202902
 
10.0%
T 601451
 
5.0%
Z 601451
 
5.0%
4 455860
 
3.8%
3 439973
 
3.7%
5 428273
 
3.6%
Other values (4) 782939
 
6.5%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:03.953225image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters35485609
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 601451
14.3%
museum 601451
14.3%
of 601451
14.3%
natural 601451
14.3%
history 601451
14.3%
smithsonian 601451
14.3%
institution 601451
14.3%
2025-01-07T10:47:04.072876image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4210157
11.9%
i 3608706
10.2%
3608706
10.2%
o 3007255
 
8.5%
a 3007255
 
8.5%
n 3007255
 
8.5%
s 2405804
 
6.8%
u 2405804
 
6.8%
N 1202902
 
3.4%
m 1202902
 
3.4%
Other values (11) 7818863
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35485609
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 4210157
11.9%
i 3608706
10.2%
3608706
10.2%
o 3007255
 
8.5%
a 3007255
 
8.5%
n 3007255
 
8.5%
s 2405804
 
6.8%
u 2405804
 
6.8%
N 1202902
 
3.4%
m 1202902
 
3.4%
Other values (11) 7818863
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35485609
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 4210157
11.9%
i 3608706
10.2%
3608706
10.2%
o 3007255
 
8.5%
a 3007255
 
8.5%
n 3007255
 
8.5%
s 2405804
 
6.8%
u 2405804
 
6.8%
N 1202902
 
3.4%
m 1202902
 
3.4%
Other values (11) 7818863
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35485609
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 4210157
11.9%
i 3608706
10.2%
3608706
10.2%
o 3007255
 
8.5%
a 3007255
 
8.5%
n 3007255
 
8.5%
s 2405804
 
6.8%
u 2405804
 
6.8%
N 1202902
 
3.4%
m 1202902
 
3.4%
Other values (11) 7818863
22.0%

references
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

rightsHolder
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

type
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct50
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.164010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length28.8108624
Min length2

Characters and Unicode

Total characters17328322
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 596967
99.3%
nsmt 977
 
0.2%
uam 775
 
0.1%
nrm 386
 
0.1%
rmnh 354
 
0.1%
rcs 246
 
< 0.1%
nmv 238
 
< 0.1%
nmsz 188
 
< 0.1%
zmmu 179
 
< 0.1%
fcmm 127
 
< 0.1%
Other values (40) 1015
 
0.2%
2025-01-07T10:47:04.282906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 2387868
13.8%
o 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
s 596967
 
3.4%
n 596967
 
3.4%
u 596967
 
3.4%
b 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
: 2387868
13.8%
o 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
s 596967
 
3.4%
n 596967
 
3.4%
u 596967
 
3.4%
b 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
: 2387868
13.8%
o 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
s 596967
 
3.4%
n 596967
 
3.4%
u 596967
 
3.4%
b 596967
 
3.4%
Other values (31) 4792015
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17328322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
: 2387868
13.8%
o 2387868
13.8%
l 1790901
 
10.3%
i 1193934
 
6.9%
r 1193934
 
6.9%
c 1193934
 
6.9%
s 596967
 
3.4%
n 596967
 
3.4%
u 596967
 
3.4%
b 596967
 
3.4%
Other values (31) 4792015
27.7%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.342692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters27065295
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
2nd rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
3rd rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
4th rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
5th rowurn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22
ValueCountFrequency (%)
urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22 601451
100.0%
2025-01-07T10:47:04.451751image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 3007255
 
11.1%
5 2405804
 
8.9%
- 2405804
 
8.9%
e 1804353
 
6.7%
u 1804353
 
6.7%
6 1804353
 
6.7%
2 1202902
 
4.4%
b 1202902
 
4.4%
1 1202902
 
4.4%
d 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
5 2405804
 
8.9%
- 2405804
 
8.9%
e 1804353
 
6.7%
u 1804353
 
6.7%
6 1804353
 
6.7%
2 1202902
 
4.4%
b 1202902
 
4.4%
1 1202902
 
4.4%
d 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
5 2405804
 
8.9%
- 2405804
 
8.9%
e 1804353
 
6.7%
u 1804353
 
6.7%
6 1804353
 
6.7%
2 1202902
 
4.4%
b 1202902
 
4.4%
1 1202902
 
4.4%
d 1202902
 
4.4%
Other values (12) 9021765
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27065295
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 3007255
 
11.1%
5 2405804
 
8.9%
- 2405804
 
8.9%
e 1804353
 
6.7%
u 1804353
 
6.7%
6 1804353
 
6.7%
2 1202902
 
4.4%
b 1202902
 
4.4%
1 1202902
 
4.4%
d 1202902
 
4.4%
Other values (12) 9021765
33.3%

datasetID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct50
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.512176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.997244996
Min length2

Characters and Unicode

Total characters2404147
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 596967
99.3%
nsmt 977
 
0.2%
uam 775
 
0.1%
nrm 386
 
0.1%
rmnh 354
 
0.1%
rcs 246
 
< 0.1%
nmv 238
 
< 0.1%
nmsz 188
 
< 0.1%
zmmu 179
 
< 0.1%
fcmm 127
 
< 0.1%
Other values (40) 1015
 
0.2%
2025-01-07T10:47:04.635813image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2404147
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 601351
25.0%
N 599550
24.9%
S 598763
24.9%
U 598142
24.9%
A 1319
 
0.1%
R 1035
 
< 0.1%
T 978
 
< 0.1%
C 551
 
< 0.1%
H 550
 
< 0.1%
Z 467
 
< 0.1%
Other values (13) 1441
 
0.1%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.679327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2405804
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMAMM
2nd rowMAMM
3rd rowMAMM
4th rowMAMM
5th rowMAMM
ValueCountFrequency (%)
mamm 601451
100.0%
2025-01-07T10:47:04.776843image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2405804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 1804353
75.0%
A 601451
 
25.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.820297image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11427569
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 601451
33.3%
extant 601451
33.3%
biology 601451
33.3%
2025-01-07T10:47:04.915249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1202902
 
10.5%
t 1202902
 
10.5%
1202902
 
10.5%
o 1202902
 
10.5%
H 601451
 
5.3%
E 601451
 
5.3%
M 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
B 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
t 1202902
 
10.5%
1202902
 
10.5%
o 1202902
 
10.5%
H 601451
 
5.3%
E 601451
 
5.3%
M 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
B 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
t 1202902
 
10.5%
1202902
 
10.5%
o 1202902
 
10.5%
H 601451
 
5.3%
E 601451
 
5.3%
M 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
B 601451
 
5.3%
Other values (5) 3007255
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11427569
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1202902
 
10.5%
t 1202902
 
10.5%
1202902
 
10.5%
o 1202902
 
10.5%
H 601451
 
5.3%
E 601451
 
5.3%
M 601451
 
5.3%
x 601451
 
5.3%
a 601451
 
5.3%
B 601451
 
5.3%
Other values (5) 3007255
26.3%

ownerInstitutionCode
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:04.964763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.95205428
Min length17

Characters and Unicode

Total characters10797281
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESERVED_SPECIMEN
2nd rowPRESERVED_SPECIMEN
3rd rowPRESERVED_SPECIMEN
4th rowPRESERVED_SPECIMEN
5th rowHUMAN_OBSERVATION
ValueCountFrequency (%)
preserved_specimen 572614
95.2%
human_observation 28837
 
4.8%
2025-01-07T10:47:05.070144image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 2891907
26.8%
S 1174065
10.9%
R 1174065
10.9%
P 1145228
 
10.6%
N 630288
 
5.8%
_ 601451
 
5.6%
I 601451
 
5.6%
M 601451
 
5.6%
V 601451
 
5.6%
C 572614
 
5.3%
Other values (7) 803310
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10797281
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 2891907
26.8%
S 1174065
10.9%
R 1174065
10.9%
P 1145228
 
10.6%
N 630288
 
5.8%
_ 601451
 
5.6%
I 601451
 
5.6%
M 601451
 
5.6%
V 601451
 
5.6%
C 572614
 
5.3%
Other values (7) 803310
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10797281
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 2891907
26.8%
S 1174065
10.9%
R 1174065
10.9%
P 1145228
 
10.6%
N 630288
 
5.8%
_ 601451
 
5.6%
I 601451
 
5.6%
M 601451
 
5.6%
V 601451
 
5.6%
C 572614
 
5.3%
Other values (7) 803310
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10797281
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 2891907
26.8%
S 1174065
10.9%
R 1174065
10.9%
P 1145228
 
10.6%
N 630288
 
5.8%
_ 601451
 
5.6%
I 601451
 
5.6%
M 601451
 
5.6%
V 601451
 
5.6%
C 572614
 
5.3%
Other values (7) 803310
 
7.4%

informationWithheld
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

dataGeneralizations
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

dynamicProperties
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

occurrenceID
Text

Unique 

Distinct601451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:05.386846image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters37891413
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique601451 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3ebec6a7f-5e95-4543-b061-6d73d80dd2ee
2nd rowhttp://n2t.net/ark:/65665/3ec070d5d-1893-4600-afa5-e56695ff219b
3rd rowhttp://n2t.net/ark:/65665/3002acaf9-9788-4539-8883-fe6bfd5f8d88
4th rowhttp://n2t.net/ark:/65665/300553499-1544-460e-9507-55ada241f992
5th rowhttp://n2t.net/ark:/65665/3005a3503-9c20-443c-899a-559e550dc71e
ValueCountFrequency (%)
http://n2t.net/ark:/65665/300aee112-891b-42e5-9bde-fec58dcc401c 1
 
< 0.1%
http://n2t.net/ark:/65665/3ba4d8f57-6417-476a-b53f-b9f5aaae7c2a 1
 
< 0.1%
http://n2t.net/ark:/65665/3ebec6a7f-5e95-4543-b061-6d73d80dd2ee 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec070d5d-1893-4600-afa5-e56695ff219b 1
 
< 0.1%
http://n2t.net/ark:/65665/3002acaf9-9788-4539-8883-fe6bfd5f8d88 1
 
< 0.1%
http://n2t.net/ark:/65665/300553499-1544-460e-9507-55ada241f992 1
 
< 0.1%
http://n2t.net/ark:/65665/3005a3503-9c20-443c-899a-559e550dc71e 1
 
< 0.1%
http://n2t.net/ark:/65665/300664e6c-5334-4a8e-b9a7-4d84389595e0 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec490be3-5856-40bf-8ec7-7c1aee651f77 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec5bfc34-61a0-47db-afb9-ff2c9a6a8961 1
 
< 0.1%
Other values (601441) 601441
> 99.9%
2025-01-07T10:47:05.740333image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37891413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 3007255
 
7.9%
6 2930823
 
7.7%
- 2405804
 
6.3%
t 2405804
 
6.3%
5 2330760
 
6.2%
a 1878835
 
5.0%
e 1729856
 
4.6%
2 1729289
 
4.6%
3 1728046
 
4.6%
4 1727823
 
4.6%
Other values (16) 16017118
42.3%
Distinct601428
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:06.153655image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length11
Mean length10.92069179
Min length4

Characters and Unicode

Total characters6568261
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique601407 ?
Unique (%)> 99.9%

Sample

1st rowUSNM 449558
2nd rowUSNM 226903
3rd rowUSNM 386480
4th rowUSNM 68620
5th rowUSNM MME9342
ValueCountFrequency (%)
usnm 596967
49.8%
wam 63
 
< 0.1%
mb 40
 
< 0.1%
zin 21
 
< 0.1%
lacm 18
 
< 0.1%
nsmt 12
 
< 0.1%
sama 6
 
< 0.1%
zmmu 5
 
< 0.1%
ncsm 4
 
< 0.1%
rmnh 4
 
< 0.1%
Other values (601439) 601471
50.2%
2025-01-07T10:47:06.596983image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6568261
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 627122
9.5%
S 616877
 
9.4%
N 601401
 
9.2%
U 598144
 
9.1%
597160
 
9.1%
1 405808
 
6.2%
2 403390
 
6.1%
3 394478
 
6.0%
5 393693
 
6.0%
4 379861
 
5.8%
Other values (25) 1550327
23.6%

recordNumber
Text

Missing 

Distinct172937
Distinct (%)31.4%
Missing50821
Missing (%)8.4%
Memory size4.6 MiB
2025-01-07T10:47:06.817081image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length28
Mean length5.176632221
Min length1

Characters and Unicode

Total characters2850409
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147848 ?
Unique (%)26.9%

Sample

1st rowFMG 2371
2nd row142/19534X
3rd row07960
4th row6459
5th rowB47586/R50468
ValueCountFrequency (%)
no 47434
 
6.9%
number 47222
 
6.9%
cohjr 5988
 
0.9%
nzp 3372
 
0.5%
psc 2713
 
0.4%
jwk 2021
 
0.3%
r 1947
 
0.3%
fm 1793
 
0.3%
jjg 1781
 
0.3%
rem 1569
 
0.2%
Other values (105383) 570874
83.1%
2025-01-07T10:47:07.102762image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2850409
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 307242
 
10.8%
2 246234
 
8.6%
3 208467
 
7.3%
4 190900
 
6.7%
0 182605
 
6.4%
5 181877
 
6.4%
6 173588
 
6.1%
7 165796
 
5.8%
8 159989
 
5.6%
9 153227
 
5.4%
Other values (69) 880484
30.9%

recordedBy
Text

Missing 

Distinct17644
Distinct (%)3.2%
Missing55563
Missing (%)9.2%
Memory size4.6 MiB
2025-01-07T10:47:07.312008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length124
Median length114
Mean length11.92282483
Min length1

Characters and Unicode

Total characters6508527
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9079 ?
Unique (%)1.7%

Sample

1st rowF. Greenwell
2nd rowJ. Silver
3rd rowSmithsonian Venezuelan Project
4th rowNelson & E. Goldman
5th rowW. Bowen & V. Thayer
ValueCountFrequency (%)
j 60783
 
4.7%
e 54366
 
4.2%
c 53496
 
4.2%
50457
 
3.9%
r 49868
 
3.9%
a 44074
 
3.4%
w 37880
 
2.9%
h 30720
 
2.4%
d 24753
 
1.9%
m 23831
 
1.9%
Other values (10447) 856734
66.6%
2025-01-07T10:47:07.592411image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6508527
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
741074
 
11.4%
e 563544
 
8.7%
. 539103
 
8.3%
n 389678
 
6.0%
a 341353
 
5.2%
o 335107
 
5.1%
r 327053
 
5.0%
l 295446
 
4.5%
i 245022
 
3.8%
s 228632
 
3.5%
Other values (70) 2502515
38.4%

recordedByID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

individualCount
Real number (ℝ)

Skewed 

Distinct21
Distinct (%)< 0.1%
Missing44
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.004351462
Minimum1
Maximum1500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:07.660930image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1500
Range1499
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.007623245
Coefficient of variation (CV)1.998924998
Kurtosis517921.2984
Mean1.004351462
Median Absolute Deviation (MAD)0
Skewness700.9743605
Sum604024
Variance4.030551096
MonotonicityNot monotonic
2025-01-07T10:47:07.714555image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 601314
> 99.9%
2 45
 
< 0.1%
6 8
 
< 0.1%
3 8
 
< 0.1%
4 6
 
< 0.1%
7 5
 
< 0.1%
5 4
 
< 0.1%
11 2
 
< 0.1%
271 2
 
< 0.1%
20 2
 
< 0.1%
Other values (11) 11
 
< 0.1%
(Missing) 44
 
< 0.1%
ValueCountFrequency (%)
1 601314
> 99.9%
2 45
 
< 0.1%
3 8
 
< 0.1%
4 6
 
< 0.1%
5 4
 
< 0.1%
ValueCountFrequency (%)
1500 1
< 0.1%
271 2
< 0.1%
150 1
< 0.1%
60 1
< 0.1%
47 1
< 0.1%

organismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

organismQuantityType
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

sex
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing88216
Missing (%)14.7%
Memory size4.6 MiB
2025-01-07T10:47:07.752558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.961610179
Min length4

Characters and Unicode

Total characters2546472
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMALE
2nd rowMALE
3rd rowMALE
4th rowFEMALE
5th rowFEMALE
ValueCountFrequency (%)
male 266469
51.9%
female 246766
48.1%
2025-01-07T10:47:07.854329image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 760001
29.8%
M 513235
20.2%
A 513235
20.2%
L 513235
20.2%
F 246766
 
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2546472
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 760001
29.8%
M 513235
20.2%
A 513235
20.2%
L 513235
20.2%
F 246766
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2546472
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 760001
29.8%
M 513235
20.2%
A 513235
20.2%
L 513235
20.2%
F 246766
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2546472
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 760001
29.8%
M 513235
20.2%
A 513235
20.2%
L 513235
20.2%
F 246766
 
9.7%

lifeStage
Text

Missing 

Distinct10
Distinct (%)< 0.1%
Missing550088
Missing (%)91.5%
Memory size4.6 MiB
2025-01-07T10:47:07.902004image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length5
Mean length6.093024161
Min length5

Characters and Unicode

Total characters312956
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAdult
2nd rowAdult
3rd rowJuvenile
4th rowJuvenile
5th rowAdult
ValueCountFrequency (%)
adult 31097
60.5%
juvenile 11486
 
22.4%
immature 3896
 
7.6%
subadult 2153
 
4.2%
embryo 983
 
1.9%
fetus 681
 
1.3%
nestling 499
 
1.0%
neonate 448
 
0.9%
mature 80
 
0.2%
unknown 40
 
0.1%
2025-01-07T10:47:08.007234image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 51546
16.5%
l 45235
14.5%
t 38854
12.4%
d 33250
10.6%
A 31097
9.9%
e 29024
9.3%
n 12553
 
4.0%
i 11985
 
3.8%
J 11486
 
3.7%
v 11486
 
3.7%
Other values (17) 36440
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 312956
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 51546
16.5%
l 45235
14.5%
t 38854
12.4%
d 33250
10.6%
A 31097
9.9%
e 29024
9.3%
n 12553
 
4.0%
i 11985
 
3.8%
J 11486
 
3.7%
v 11486
 
3.7%
Other values (17) 36440
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 312956
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 51546
16.5%
l 45235
14.5%
t 38854
12.4%
d 33250
10.6%
A 31097
9.9%
e 29024
9.3%
n 12553
 
4.0%
i 11985
 
3.8%
J 11486
 
3.7%
v 11486
 
3.7%
Other values (17) 36440
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 312956
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 51546
16.5%
l 45235
14.5%
t 38854
12.4%
d 33250
10.6%
A 31097
9.9%
e 29024
9.3%
n 12553
 
4.0%
i 11985
 
3.8%
J 11486
 
3.7%
v 11486
 
3.7%
Other values (17) 36440
11.6%

reproductiveCondition
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

caste
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

behavior
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

vitality
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

establishmentMeans
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

degreeOfEstablishment
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

pathway
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

georeferenceVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:08.051235image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4210157
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 601451
100.0%
2025-01-07T10:47:08.140161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1202902
28.6%
P 601451
14.3%
R 601451
14.3%
S 601451
14.3%
N 601451
14.3%
T 601451
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1202902
28.6%
P 601451
14.3%
R 601451
14.3%
S 601451
14.3%
N 601451
14.3%
T 601451
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1202902
28.6%
P 601451
14.3%
R 601451
14.3%
S 601451
14.3%
N 601451
14.3%
T 601451
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4210157
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1202902
28.6%
P 601451
14.3%
R 601451
14.3%
S 601451
14.3%
N 601451
14.3%
T 601451
14.3%

preparations
Text

Missing 

Distinct542
Distinct (%)0.1%
Missing26965
Missing (%)4.5%
Memory size4.6 MiB
2025-01-07T10:47:08.199042image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length73
Median length11
Mean length10.02423558
Min length4

Characters and Unicode

Total characters5758783
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)< 0.1%

Sample

1st rowSkin; Skull
2nd rowSkin; Skull
3rd rowSkin; Skull
4th rowSkin; Skull
5th rowSkin; Skull
ValueCountFrequency (%)
skull 452764
44.7%
skin 367609
36.3%
fluid 101452
 
10.0%
skeleton 36584
 
3.6%
partial 10316
 
1.0%
in 8642
 
0.9%
remainder 8641
 
0.9%
anatomical 5878
 
0.6%
baculum/baubellum 3372
 
0.3%
baleen 2349
 
0.2%
Other values (42) 14726
 
1.5%
2025-01-07T10:47:08.343287image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5758783
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1076304
18.7%
k 859539
14.9%
S 856659
14.9%
u 570461
9.9%
i 506031
8.8%
437847
7.6%
n 435543
7.6%
; 404417
 
7.0%
d 111124
 
1.9%
e 103346
 
1.8%
Other values (39) 397512
 
6.9%

disposition
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

associatedOccurrences
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

associatedReferences
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

associatedSequences
Text

Missing 

Distinct1050
Distinct (%)99.6%
Missing600397
Missing (%)99.8%
Memory size4.6 MiB
2025-01-07T10:47:08.418721image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length699
Median length49
Mean length99.59108159
Min length47

Characters and Unicode

Total characters104969
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1046 ?
Unique (%)99.2%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=AY922964;https://www.ncbi.nlm.nih.gov/gquery?term=AY922875
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KC753815;https://www.ncbi.nlm.nih.gov/gquery?term=KC753933;https://www.ncbi.nlm.nih.gov/gquery?term=KC754042;https://www.ncbi.nlm.nih.gov/gquery?term=KC754162;https://www.ncbi.nlm.nih.gov/gquery?term=KC754280
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KC011508;https://www.ncbi.nlm.nih.gov/gquery?term=KC011594;https://www.ncbi.nlm.nih.gov/gquery?term=KC011682
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MN707485;https://www.ncbi.nlm.nih.gov/gquery?term=MN707432
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ317640;https://www.ncbi.nlm.nih.gov/gquery?term=JQ317668
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=kx998919 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=eu021073 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=eu021074 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=fj383131 2
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=jq316929;https://www.ncbi.nlm.nih.gov/gquery?term=jq316833 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mn326038 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq317640;https://www.ncbi.nlm.nih.gov/gquery?term=jq317668 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jx020578 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=op432689 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ky472359 1
 
0.1%
Other values (1040) 1040
98.7%
2025-01-07T10:47:08.559471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8515
 
8.1%
t 6360
 
6.1%
w 6360
 
6.1%
/ 6360
 
6.1%
n 6360
 
6.1%
h 4240
 
4.0%
e 4240
 
4.0%
g 4240
 
4.0%
m 4240
 
4.0%
i 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
t 6360
 
6.1%
w 6360
 
6.1%
/ 6360
 
6.1%
n 6360
 
6.1%
h 4240
 
4.0%
e 4240
 
4.0%
g 4240
 
4.0%
m 4240
 
4.0%
i 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
t 6360
 
6.1%
w 6360
 
6.1%
/ 6360
 
6.1%
n 6360
 
6.1%
h 4240
 
4.0%
e 4240
 
4.0%
g 4240
 
4.0%
m 4240
 
4.0%
i 4240
 
4.0%
Other values (48) 49814
47.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 104969
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 8515
 
8.1%
t 6360
 
6.1%
w 6360
 
6.1%
/ 6360
 
6.1%
n 6360
 
6.1%
h 4240
 
4.0%
e 4240
 
4.0%
g 4240
 
4.0%
m 4240
 
4.0%
i 4240
 
4.0%
Other values (48) 49814
47.5%

associatedTaxa
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

otherCatalogNumbers
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

occurrenceRemarks
Text

Missing 

Distinct5322
Distinct (%)49.3%
Missing590662
Missing (%)98.2%
Memory size4.6 MiB
2025-01-07T10:47:08.773687image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44804
Median length2082
Mean length214.0076003
Min length4

Characters and Unicode

Total characters2308928
Distinct characters158
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4721 ?
Unique (%)43.8%

Sample

1st rowFrom ledger catalogue 577876-577900: "field data recorded from field catalogues"
2nd rowSkin found in rotunda hallway hold-up case, 2017. May need tanning before installation into collection.
3rd rowLectotype designated by Avila Pires (1968:163).
4th rowSkull removed from alcoholic specimen.
5th rowMore than 800 dolphins stranded along a 220 km stretch pof the coast of Peru. See STR18239.; Broccetto, Marilia CNN website 22 IV 2012
ValueCountFrequency (%)
the 13880
 
3.8%
of 9359
 
2.6%
and 7684
 
2.1%
in 7077
 
1.9%
for 6435
 
1.8%
to 6041
 
1.6%
4896
 
1.3%
on 4761
 
1.3%
was 4231
 
1.2%
from 3875
 
1.1%
Other values (19019) 298259
81.4%
2025-01-07T10:47:09.053249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2308928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
355709
15.4%
e 205843
 
8.9%
a 147185
 
6.4%
t 125245
 
5.4%
o 122482
 
5.3%
n 120296
 
5.2%
i 111994
 
4.9%
s 111800
 
4.8%
r 110930
 
4.8%
l 77896
 
3.4%
Other values (148) 819548
35.5%

organismID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

organismName
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

organismScope
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

associatedOrganisms
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

previousIdentifications
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

organismRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

materialEntityID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

materialEntityRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

verbatimLabel
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

materialSampleID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

eventID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

parentEventID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

eventType
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

fieldNumber
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

eventDate
Text

Missing 

Distinct46549
Distinct (%)8.1%
Missing28480
Missing (%)4.7%
Memory size4.6 MiB
2025-01-07T10:47:09.272906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.72325999
Min length4

Characters and Unicode

Total characters5571146
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7620 ?
Unique (%)1.3%

Sample

1st row1989-02-28
2nd row1917-08-08
3rd row1966-05
4th row1894-07-15
5th row1992-11-05
ValueCountFrequency (%)
1968 1161
 
0.2%
1959 829
 
0.1%
1965-06 704
 
0.1%
1966-06-02 682
 
0.1%
1903 600
 
0.1%
1905 591
 
0.1%
1965 543
 
0.1%
1967-08 537
 
0.1%
1967-05 529
 
0.1%
1968-09-02 520
 
0.1%
Other values (46539) 566275
98.8%
2025-01-07T10:47:09.568961image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1091809
19.6%
1 1091166
19.6%
0 832958
15.0%
9 716794
12.9%
2 391838
 
7.0%
6 323354
 
5.8%
8 308610
 
5.5%
7 251407
 
4.5%
3 195450
 
3.5%
5 191688
 
3.4%
Other values (2) 176072
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5571146
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 1091809
19.6%
1 1091166
19.6%
0 832958
15.0%
9 716794
12.9%
2 391838
 
7.0%
6 323354
 
5.8%
8 308610
 
5.5%
7 251407
 
4.5%
3 195450
 
3.5%
5 191688
 
3.4%
Other values (2) 176072
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5571146
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 1091809
19.6%
1 1091166
19.6%
0 832958
15.0%
9 716794
12.9%
2 391838
 
7.0%
6 323354
 
5.8%
8 308610
 
5.5%
7 251407
 
4.5%
3 195450
 
3.5%
5 191688
 
3.4%
Other values (2) 176072
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5571146
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 1091809
19.6%
1 1091166
19.6%
0 832958
15.0%
9 716794
12.9%
2 391838
 
7.0%
6 323354
 
5.8%
8 308610
 
5.5%
7 251407
 
4.5%
3 195450
 
3.5%
5 191688
 
3.4%
Other values (2) 176072
 
3.2%

eventTime
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

startDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing67487
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean176.2988872
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:09.647413image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q194
median178
Q3252
95-th percentile338
Maximum366
Range365
Interquartile range (IQR)158

Descriptive statistics

Standard deviation96.99817854
Coefficient of variation (CV)0.5501916665
Kurtosis-1.018777552
Mean176.2988872
Median Absolute Deviation (MAD)79
Skewness0.05806035056
Sum94137259
Variance9408.64664
MonotonicityNot monotonic
2025-01-07T10:47:09.712961image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193 2428
 
0.4%
222 2369
 
0.4%
199 2342
 
0.4%
205 2305
 
0.4%
207 2235
 
0.4%
208 2179
 
0.4%
197 2151
 
0.4%
202 2126
 
0.4%
203 2117
 
0.4%
201 2091
 
0.3%
Other values (356) 511621
85.1%
(Missing) 67487
 
11.2%
ValueCountFrequency (%)
1 715
0.1%
2 756
0.1%
3 876
0.1%
4 830
0.1%
5 946
0.2%
ValueCountFrequency (%)
366 156
 
< 0.1%
365 665
0.1%
364 811
0.1%
363 876
0.1%
362 887
0.1%

endDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing67487
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean176.3304867
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:09.777513image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q194
median178
Q3252
95-th percentile338
Maximum366
Range365
Interquartile range (IQR)158

Descriptive statistics

Standard deviation96.99421498
Coefficient of variation (CV)0.5500705907
Kurtosis-1.018929854
Mean176.3304867
Median Absolute Deviation (MAD)79
Skewness0.05758247819
Sum94154132
Variance9407.87774
MonotonicityNot monotonic
2025-01-07T10:47:09.841128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
222 2369
 
0.4%
193 2355
 
0.4%
199 2343
 
0.4%
205 2304
 
0.4%
207 2253
 
0.4%
208 2179
 
0.4%
197 2150
 
0.4%
204 2149
 
0.4%
202 2125
 
0.4%
203 2117
 
0.4%
Other values (356) 511620
85.1%
(Missing) 67487
 
11.2%
ValueCountFrequency (%)
1 715
0.1%
2 756
0.1%
3 875
0.1%
4 830
0.1%
5 947
0.2%
ValueCountFrequency (%)
366 156
 
< 0.1%
365 665
0.1%
364 811
0.1%
363 876
0.1%
362 887
0.1%

year
Real number (ℝ)

Missing 

Distinct350
Distinct (%)0.1%
Missing28519
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean1943.86398
Minimum1519
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:09.906270image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1519
5-th percentile1892
Q11909
median1959
Q31969
95-th percentile1991
Maximum2023
Range504
Interquartile range (IQR)60

Descriptive statistics

Standard deviation34.91862388
Coefficient of variation (CV)0.01796351197
Kurtosis0.3579592988
Mean1943.86398
Median Absolute Deviation (MAD)23
Skewness-0.4490607749
Sum1113701878
Variance1219.310294
MonotonicityNot monotonic
2025-01-07T10:47:09.970776image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1967 30814
 
5.1%
1968 27037
 
4.5%
1966 22575
 
3.8%
1969 15259
 
2.5%
1965 12690
 
2.1%
1964 12541
 
2.1%
1962 11208
 
1.9%
1970 10525
 
1.7%
1916 9955
 
1.7%
1963 9798
 
1.6%
Other values (340) 410530
68.3%
(Missing) 28519
 
4.7%
ValueCountFrequency (%)
1519 1
< 0.1%
1520 1
< 0.1%
1526 1
< 0.1%
1531 1
< 0.1%
1532 2
< 0.1%
ValueCountFrequency (%)
2023 74
< 0.1%
2022 67
< 0.1%
2021 6
 
< 0.1%
2020 8
 
< 0.1%
2019 91
< 0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)< 0.1%
Missing45368
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean6.302123964
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:10.023500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.191651108
Coefficient of variation (CV)0.5064405471
Kurtosis-1.020952363
Mean6.302123964
Median Absolute Deviation (MAD)3
Skewness0.04806755424
Sum3504504
Variance10.18663679
MonotonicityNot monotonic
2025-01-07T10:47:10.072007image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 63530
10.6%
8 55595
9.2%
6 55446
9.2%
3 50980
8.5%
5 50113
8.3%
4 46748
7.8%
9 43982
7.3%
2 43057
7.2%
10 40456
6.7%
1 39414
6.6%
Other values (2) 66762
11.1%
(Missing) 45368
7.5%
ValueCountFrequency (%)
1 39414
6.6%
2 43057
7.2%
3 50980
8.5%
4 46748
7.8%
5 50113
8.3%
ValueCountFrequency (%)
12 31553
5.2%
11 35209
5.9%
10 40456
6.7%
9 43982
7.3%
8 55595
9.2%

day
Real number (ℝ)

Missing 

Distinct31
Distinct (%)< 0.1%
Missing68254
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean15.71641626
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:10.121691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.709201082
Coefficient of variation (CV)0.5541467558
Kurtosis-1.179848024
Mean15.71641626
Median Absolute Deviation (MAD)7
Skewness0.001251858677
Sum8379946
Variance75.85018349
MonotonicityNot monotonic
2025-01-07T10:47:10.173197image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
10 19183
 
3.2%
20 18565
 
3.1%
22 18462
 
3.1%
15 18330
 
3.0%
18 18186
 
3.0%
14 17946
 
3.0%
5 17919
 
3.0%
16 17902
 
3.0%
27 17827
 
3.0%
21 17778
 
3.0%
Other values (21) 351099
58.4%
(Missing) 68254
 
11.3%
ValueCountFrequency (%)
1 16662
2.8%
2 17650
2.9%
3 16942
2.8%
4 16610
2.8%
5 17919
3.0%
ValueCountFrequency (%)
31 8707
1.4%
30 15441
2.6%
29 15800
2.6%
28 17199
2.9%
27 17827
3.0%

verbatimEventDate
Text

Missing 

Distinct45124
Distinct (%)8.0%
Missing36490
Missing (%)6.1%
Memory size4.6 MiB
2025-01-07T10:47:10.361100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length82
Median length11
Mean length10.73425953
Min length3

Characters and Unicode

Total characters6064438
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7925 ?
Unique (%)1.4%

Sample

1st row28 Feb 1989
2nd row8 Aug 1917
3rd row-- May 1966
4th row15 Jul 1894
5th row5 Nov 1992
ValueCountFrequency (%)
119289
 
7.0%
jul 59029
 
3.5%
aug 52663
 
3.1%
jun 52253
 
3.1%
mar 49098
 
2.9%
may 47959
 
2.8%
apr 45015
 
2.6%
sep 41961
 
2.5%
feb 40432
 
2.4%
oct 39123
 
2.3%
Other values (873) 1153619
67.8%
2025-01-07T10:47:10.647075image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6064438
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1135480
18.7%
1 869039
14.3%
9 644744
 
10.6%
2 290400
 
4.8%
- 284559
 
4.7%
6 256804
 
4.2%
8 242113
 
4.0%
7 176263
 
2.9%
u 165038
 
2.7%
0 163304
 
2.7%
Other values (65) 1836694
30.3%

habitat
Text

Missing 

Distinct7512
Distinct (%)5.7%
Missing468915
Missing (%)78.0%
Memory size4.6 MiB
2025-01-07T10:47:10.861210image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1014
Median length694
Mean length27.3692808
Min length1

Characters and Unicode

Total characters3627415
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4415 ?
Unique (%)3.3%

Sample

1st rowEcological remarks by collector(s): yes
2nd rowPremontane very humid forest
3rd rowEcological remarks by collector(s): no
4th rowEcological remarks by collector(s): yes
5th rowCulvert
ValueCountFrequency (%)
by 49297
 
9.4%
ecological 48727
 
9.3%
remarks 48718
 
9.3%
collector(s 48716
 
9.3%
yes 41564
 
8.0%
forest 32139
 
6.2%
tropical 15058
 
2.9%
humid 14768
 
2.8%
no 7275
 
1.4%
in 6943
 
1.3%
Other values (3497) 208498
40.0%
2025-01-07T10:47:11.133849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3627415
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
389167
 
10.7%
o 316538
 
8.7%
e 293307
 
8.1%
r 281112
 
7.7%
l 253946
 
7.0%
s 244547
 
6.7%
c 240040
 
6.6%
a 233816
 
6.4%
i 137021
 
3.8%
t 136017
 
3.7%
Other values (76) 1101904
30.4%

samplingProtocol
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

sampleSizeValue
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

sampleSizeUnit
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

samplingEffort
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

fieldNotes
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

eventRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

locationID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

higherGeographyID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct8925
Distinct (%)1.5%
Missing440
Missing (%)0.1%
Memory size4.6 MiB
2025-01-07T10:47:11.338076image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length146
Median length124
Mean length39.09340095
Min length4

Characters and Unicode

Total characters23495564
Distinct characters91
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3023 ?
Unique (%)0.5%

Sample

1st rowNorth America, Panama, Bocas Del Toro
2nd rowNorth America, United States, Utah
3rd rowSouth America, Venezuela, Bolivar
4th rowNorth America, Mexico, Oaxaca
5th rowNorth America, North Atlantic Ocean, United States, North Carolina, Carteret
ValueCountFrequency (%)
america 390243
 
12.4%
north 378352
 
12.1%
united 229925
 
7.3%
states 225212
 
7.2%
africa 111667
 
3.6%
south 90792
 
2.9%
county 80759
 
2.6%
asia 66157
 
2.1%
ocean 58408
 
1.9%
mexico 50692
 
1.6%
Other values (5566) 1452640
46.3%
2025-01-07T10:47:11.617082image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23495564
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2533836
 
10.8%
a 2342309
 
10.0%
i 1683292
 
7.2%
t 1628350
 
6.9%
e 1586909
 
6.8%
r 1444280
 
6.1%
, 1372561
 
5.8%
o 1263879
 
5.4%
n 1236327
 
5.3%
c 879180
 
3.7%
Other values (81) 7524641
32.0%

continent
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing39181
Missing (%)6.5%
Memory size4.6 MiB
2025-01-07T10:47:11.681417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.4674249
Min length4

Characters and Unicode

Total characters5885519
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowSOUTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 305548
54.3%
africa 100847
 
17.9%
south_america 70554
 
12.5%
asia 64472
 
11.5%
europe 13203
 
2.3%
oceania 7485
 
1.3%
antarctica 161
 
< 0.1%
2025-01-07T10:47:11.791657image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1098295
18.7%
R 795861
13.5%
I 549067
9.3%
C 484756
8.2%
E 409993
 
7.0%
O 396790
 
6.7%
T 376424
 
6.4%
H 376102
 
6.4%
_ 376102
 
6.4%
M 376102
 
6.4%
Other values (5) 646027
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5885519
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1098295
18.7%
R 795861
13.5%
I 549067
9.3%
C 484756
8.2%
E 409993
 
7.0%
O 396790
 
6.7%
T 376424
 
6.4%
H 376102
 
6.4%
_ 376102
 
6.4%
M 376102
 
6.4%
Other values (5) 646027
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5885519
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1098295
18.7%
R 795861
13.5%
I 549067
9.3%
C 484756
8.2%
E 409993
 
7.0%
O 396790
 
6.7%
T 376424
 
6.4%
H 376102
 
6.4%
_ 376102
 
6.4%
M 376102
 
6.4%
Other values (5) 646027
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5885519
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1098295
18.7%
R 795861
13.5%
I 549067
9.3%
C 484756
8.2%
E 409993
 
7.0%
O 396790
 
6.7%
T 376424
 
6.4%
H 376102
 
6.4%
_ 376102
 
6.4%
M 376102
 
6.4%
Other values (5) 646027
11.0%

waterBody
Text

Missing 

Distinct1298
Distinct (%)2.1%
Missing539858
Missing (%)89.8%
Memory size4.6 MiB
2025-01-07T10:47:11.978468image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length79
Median length75
Mean length24.02534379
Min length6

Characters and Unicode

Total characters1479793
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique776 ?
Unique (%)1.3%

Sample

1st rowNorth Atlantic Ocean
2nd rowNorth Pacific Ocean, Bering Sea
3rd rowNorth Pacific Ocean
4th rowNorth Atlantic Ocean, Gulf Of Mexico
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 58130
25.3%
north 49957
21.8%
atlantic 30063
13.1%
pacific 21536
 
9.4%
sea 8710
 
3.8%
of 8285
 
3.6%
gulf 7277
 
3.2%
mexico 6087
 
2.7%
south 3736
 
1.6%
indian 3443
 
1.5%
Other values (1047) 32100
14.0%
2025-01-07T10:47:12.245047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1479793
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
167731
11.3%
a 149650
 
10.1%
c 142458
 
9.6%
t 125319
 
8.5%
n 116971
 
7.9%
i 97425
 
6.6%
e 90274
 
6.1%
o 70318
 
4.8%
O 66128
 
4.5%
r 64946
 
4.4%
Other values (51) 388573
26.3%

islandGroup
Text

Missing 

Distinct68
Distinct (%)1.4%
Missing596682
Missing (%)99.2%
Memory size4.6 MiB
2025-01-07T10:47:12.327107image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length24
Mean length13.28538478
Min length8

Characters and Unicode

Total characters63358
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.4%

Sample

1st rowPribilof Islands
2nd rowPribilof Islands
3rd rowRyukyu Islands
4th rowPribilof Islands
5th rowBatan Islands
ValueCountFrequency (%)
islands 3374
40.8%
pribilof 1808
21.9%
moluccas 1194
 
14.4%
ryukyu 497
 
6.0%
babuyan 176
 
2.1%
channel 159
 
1.9%
batan 120
 
1.5%
nicobar 108
 
1.3%
bismarck 94
 
1.1%
yap 83
 
1.0%
Other values (66) 653
 
7.9%
2025-01-07T10:47:12.622306image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 63358
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 8103
12.8%
l 6718
 
10.6%
a 6381
 
10.1%
n 4444
 
7.0%
i 4222
 
6.7%
d 3521
 
5.6%
3497
 
5.5%
I 3376
 
5.3%
o 3353
 
5.3%
c 2688
 
4.2%
Other values (36) 17055
26.9%

island
Text

Missing 

Distinct345
Distinct (%)0.9%
Missing564842
Missing (%)93.9%
Memory size4.6 MiB
2025-01-07T10:47:12.829631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length21
Mean length8.146903767
Min length1

Characters and Unicode

Total characters298250
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)0.3%

Sample

1st rowSt. Paul Island
2nd rowSt. Paul Island
3rd rowTrinidad
4th rowBorneo
5th rowCulion Island
ValueCountFrequency (%)
island 7184
14.8%
borneo 5932
 
12.2%
sumatra 3675
 
7.5%
luzon 3124
 
6.4%
java 3005
 
6.2%
celebes 2678
 
5.5%
trinidad 2605
 
5.4%
st 1818
 
3.7%
paul 1799
 
3.7%
honshu 1290
 
2.6%
Other values (366) 15576
32.0%
2025-01-07T10:47:13.094128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 298250
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 39564
13.3%
n 28846
 
9.7%
o 23778
 
8.0%
e 21049
 
7.1%
r 16512
 
5.5%
d 15796
 
5.3%
l 15656
 
5.2%
s 14538
 
4.9%
u 14063
 
4.7%
12077
 
4.0%
Other values (47) 96371
32.3%
Distinct221
Distinct (%)< 0.1%
Missing4662
Missing (%)0.8%
Memory size4.6 MiB
2025-01-07T10:47:13.278173image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1193578
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowPA
2nd rowUS
3rd rowVE
4th rowMX
5th rowUS
ValueCountFrequency (%)
us 226290
37.9%
mx 35569
 
6.0%
pa 25486
 
4.3%
ve 24981
 
4.2%
ca 19304
 
3.2%
co 16625
 
2.8%
id 14924
 
2.5%
zz 13450
 
2.3%
br 12246
 
2.1%
za 11853
 
2.0%
Other values (211) 196061
32.9%
2025-01-07T10:47:13.508063image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 237899
19.9%
U 236282
19.8%
A 75072
 
6.3%
M 63999
 
5.4%
C 56100
 
4.7%
E 50124
 
4.2%
P 48406
 
4.1%
Z 47388
 
4.0%
G 36679
 
3.1%
X 35577
 
3.0%
Other values (16) 306052
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1193578
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 237899
19.9%
U 236282
19.8%
A 75072
 
6.3%
M 63999
 
5.4%
C 56100
 
4.7%
E 50124
 
4.2%
P 48406
 
4.1%
Z 47388
 
4.0%
G 36679
 
3.1%
X 35577
 
3.0%
Other values (16) 306052
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1193578
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 237899
19.9%
U 236282
19.8%
A 75072
 
6.3%
M 63999
 
5.4%
C 56100
 
4.7%
E 50124
 
4.2%
P 48406
 
4.1%
Z 47388
 
4.0%
G 36679
 
3.1%
X 35577
 
3.0%
Other values (16) 306052
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1193578
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 237899
19.9%
U 236282
19.8%
A 75072
 
6.3%
M 63999
 
5.4%
C 56100
 
4.7%
E 50124
 
4.2%
P 48406
 
4.1%
Z 47388
 
4.0%
G 36679
 
3.1%
X 35577
 
3.0%
Other values (16) 306052
25.6%

stateProvince
Text

Missing 

Distinct1750
Distinct (%)0.3%
Missing93954
Missing (%)15.6%
Memory size4.6 MiB
2025-01-07T10:47:13.696022image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length27
Mean length9.156487625
Min length1

Characters and Unicode

Total characters4646890
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)0.1%

Sample

1st rowBocas Del Toro
2nd rowUtah
3rd rowBolivar
4th rowOaxaca
5th rowNorth Carolina
ValueCountFrequency (%)
california 37958
 
5.7%
new 18698
 
2.8%
alaska 18000
 
2.7%
oregon 15112
 
2.3%
province 15077
 
2.2%
arizona 13072
 
1.9%
virginia 12189
 
1.8%
washington 12057
 
1.8%
texas 11524
 
1.7%
mexico 9875
 
1.5%
Other values (1720) 507096
75.6%
2025-01-07T10:47:13.955641image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4646890
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 685721
14.8%
i 388351
 
8.4%
n 356516
 
7.7%
o 350614
 
7.5%
r 326855
 
7.0%
e 277944
 
6.0%
l 192295
 
4.1%
s 173201
 
3.7%
t 172374
 
3.7%
163161
 
3.5%
Other values (65) 1559858
33.6%

county
Text

Missing 

Distinct3194
Distinct (%)2.1%
Missing447402
Missing (%)74.4%
Memory size4.6 MiB
2025-01-07T10:47:14.170695image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length47
Median length27
Mean length13.46725393
Min length1

Characters and Unicode

Total characters2074617
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)0.4%

Sample

1st rowCarteret
2nd rowCusco
3rd rowMonterey County
4th rowGalveston
5th rowTamana Ward
ValueCountFrequency (%)
county 80697
27.5%
district 13828
 
4.7%
islands 3705
 
1.3%
division 3460
 
1.2%
san 3315
 
1.1%
province 2619
 
0.9%
schoolcraft 2179
 
0.7%
mackenzie 1966
 
0.7%
lane 1935
 
0.7%
municipality 1862
 
0.6%
Other values (2969) 178313
60.7%
2025-01-07T10:47:14.440770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2074617
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 189818
 
9.1%
o 175404
 
8.5%
t 161467
 
7.8%
a 160330
 
7.7%
139830
 
6.7%
i 120188
 
5.8%
u 116014
 
5.6%
e 111686
 
5.4%
r 102364
 
4.9%
C 99007
 
4.8%
Other values (69) 698509
33.7%

municipality
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

locality
Text

Missing 

Distinct86656
Distinct (%)15.3%
Missing35404
Missing (%)5.9%
Memory size4.6 MiB
2025-01-07T10:47:14.654986image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length294
Median length159
Mean length21.69044267
Min length1

Characters and Unicode

Total characters12277810
Distinct characters126
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52764 ?
Unique (%)9.3%

Sample

1st rowTierra Oscura, 3.5 Km S. Tiger Key
2nd rowUinta Forest, Currant Creek
3rd rowkm. 125, 85 Km SSE El Dorado
4th rowTotontepec
5th rowAtlantic Beach, Atlantic Beach, 1/2 Mi E Of Triple S Pier.
ValueCountFrequency (%)
km 82857
 
3.9%
mi 82389
 
3.8%
of 34259
 
1.6%
n 30440
 
1.4%
river 28140
 
1.3%
s 27057
 
1.3%
e 26413
 
1.2%
w 26172
 
1.2%
island 23296
 
1.1%
san 23251
 
1.1%
Other values (42744) 1760837
82.1%
2025-01-07T10:47:14.944896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1579064
 
12.9%
a 1198874
 
9.8%
e 766623
 
6.2%
i 659790
 
5.4%
n 655819
 
5.3%
o 653029
 
5.3%
r 550116
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940149
40.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198874
 
9.8%
e 766623
 
6.2%
i 659790
 
5.4%
n 655819
 
5.3%
o 653029
 
5.3%
r 550116
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940149
40.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198874
 
9.8%
e 766623
 
6.2%
i 659790
 
5.4%
n 655819
 
5.3%
o 653029
 
5.3%
r 550116
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940149
40.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12277810
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1579064
 
12.9%
a 1198874
 
9.8%
e 766623
 
6.2%
i 659790
 
5.4%
n 655819
 
5.3%
o 653029
 
5.3%
r 550116
 
4.5%
l 446951
 
3.6%
t 434393
 
3.5%
, 393002
 
3.2%
Other values (116) 4940149
40.2%

verbatimLocality
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

verbatimElevation
Text

Missing 

Distinct29
Distinct (%)1.8%
Missing599861
Missing (%)99.7%
Memory size4.6 MiB
2025-01-07T10:47:15.016886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length8
Mean length8.518867925
Min length2

Characters and Unicode

Total characters13545
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.6%

Sample

1st rowsea level
2nd rowsealevel
3rd rowsealevel
4th rowsealevel
5th rowsee Osgood 1909:214
ValueCountFrequency (%)
sealevel 1096
46.9%
sea 280
 
12.0%
level 277
 
11.9%
ft 143
 
6.1%
104
 
4.5%
100 81
 
3.5%
m 59
 
2.5%
near 32
 
1.4%
below 30
 
1.3%
accuracy 28
 
1.2%
Other values (33) 206
 
8.8%
2025-01-07T10:47:15.135304image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13545
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 4198
31.0%
l 2792
20.6%
a 1481
 
10.9%
s 1380
 
10.2%
v 1376
 
10.2%
746
 
5.5%
0 314
 
2.3%
t 156
 
1.2%
1 152
 
1.1%
f 143
 
1.1%
Other values (33) 807
 
6.0%

verticalDatum
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

verbatimDepth
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

minimumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

maximumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

locationAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

locationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

decimalLatitude
Real number (ℝ)

Missing 

Distinct10276
Distinct (%)6.7%
Missing447917
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean8.416134943
Minimum-77.92
Maximum85.68
Zeros3
Zeros (%)< 0.1%
Negative37879
Negative (%)6.3%
Memory size4.6 MiB
2025-01-07T10:47:15.198228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-77.92
5-th percentile-29.67
Q10.57
median8.87
Q326.75
95-th percentile44.0495
Maximum85.68
Range163.6
Interquartile range (IQR)26.18

Descriptive statistics

Standard deviation23.03645694
Coefficient of variation (CV)2.737177706
Kurtosis0.9275651858
Mean8.416134943
Median Absolute Deviation (MAD)10.2
Skewness-0.437373054
Sum1292162.862
Variance530.6783483
MonotonicityNot monotonic
2025-01-07T10:47:15.267744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.3 1697
 
0.3%
2.78 1090
 
0.2%
5.67 991
 
0.2%
0.88 978
 
0.2%
8.83 813
 
0.1%
10.53 811
 
0.1%
3.17 798
 
0.1%
7.32 740
 
0.1%
8.95 731
 
0.1%
10.2 721
 
0.1%
Other values (10266) 144164
 
24.0%
(Missing) 447917
74.5%
ValueCountFrequency (%)
-77.92 1
 
< 0.1%
-77.75 5
< 0.1%
-77.744 6
< 0.1%
-77.7433 1
 
< 0.1%
-77.727 2
 
< 0.1%
ValueCountFrequency (%)
85.68 1
 
< 0.1%
82.72 1
 
< 0.1%
80.9 52
< 0.1%
80.8292 1
 
< 0.1%
79.88 1
 
< 0.1%

decimalLongitude
Real number (ℝ)

Missing 

Distinct11872
Distinct (%)7.7%
Missing447917
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean-8.050285927
Minimum-180
Maximum180
Zeros9
Zeros (%)< 0.1%
Negative87899
Negative (%)14.6%
Memory size4.6 MiB
2025-01-07T10:47:15.335099image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-180
5-th percentile-97.35
Q1-69.98
median-3.55
Q329.28
95-th percentile124.0245
Maximum180
Range360
Interquartile range (IQR)99.26

Descriptive statistics

Standard deviation71.89637564
Coefficient of variation (CV)-8.930909571
Kurtosis-0.3842490882
Mean-8.050285927
Median Absolute Deviation (MAD)62.22
Skewness0.4580371033
Sum-1235992.6
Variance5169.08883
MonotonicityNot monotonic
2025-01-07T10:47:15.398744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-66.22 1723
 
0.3%
16.42 1090
 
0.2%
127.68 955
 
0.2%
-0.2 929
 
0.2%
-70.5 790
 
0.1%
-71.95 739
 
0.1%
-79.62 722
 
0.1%
0.97 651
 
0.1%
-66.18 629
 
0.1%
-69.78 625
 
0.1%
Other values (11862) 144681
 
24.1%
(Missing) 447917
74.5%
ValueCountFrequency (%)
-180 1
 
< 0.1%
-179.92 3
< 0.1%
-179.9 1
 
< 0.1%
-179.82 1
 
< 0.1%
-179.68 1
 
< 0.1%
ValueCountFrequency (%)
180 3
< 0.1%
179.97 1
 
< 0.1%
179.95 1
 
< 0.1%
179.82 1
 
< 0.1%
179.78 1
 
< 0.1%

coordinateUncertaintyInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

coordinatePrecision
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

pointRadiusSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct4
Distinct (%)< 0.1%
Missing468202
Missing (%)77.8%
Memory size4.6 MiB
2025-01-07T10:47:15.444743image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.96475771
Min length3

Characters and Unicode

Total characters3060031
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 133004
33.3%
minutes 133003
33.3%
seconds 133003
33.3%
utm 192
 
< 0.1%
unknown 53
 
< 0.1%
decimal 1
 
< 0.1%
2025-01-07T10:47:15.555827image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
D 133004
 
4.3%
i 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
D 133004
 
4.3%
i 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
D 133004
 
4.3%
i 133004
 
4.3%
Other values (12) 665563
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3060031
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 665019
21.7%
s 399010
13.0%
n 266165
 
8.7%
266007
 
8.7%
M 133195
 
4.4%
o 133056
 
4.3%
g 133004
 
4.3%
r 133004
 
4.3%
D 133004
 
4.3%
i 133004
 
4.3%
Other values (12) 665563
21.8%

verbatimSRS
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

footprintWKT
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

footprintSRS
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

footprintSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

georeferencedBy
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

georeferencedDate
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

georeferenceProtocol
Text

Missing 

Distinct8
Distinct (%)0.1%
Missing592196
Missing (%)98.5%
Memory size4.6 MiB
2025-01-07T10:47:15.609854image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length26
Median length12
Mean length10.66731496
Min length3

Characters and Unicode

Total characters98726
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowGoogle Earth
2nd rowGoogle Earth
3rd rowGPS
4th rowGoogle Earth
5th rowGoogle Earth
ValueCountFrequency (%)
google 7074
41.5%
earth 7074
41.5%
gps 1418
 
8.3%
usgs 530
 
3.1%
topoview 530
 
3.1%
gazetteer 137
 
0.8%
atlas 42
 
0.2%
of 42
 
0.2%
canada 42
 
0.2%
42
 
0.2%
Other values (4) 96
 
0.6%
2025-01-07T10:47:15.718769image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 98726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 15334
15.5%
G 9159
9.3%
e 8096
8.2%
t 8000
8.1%
7772
7.9%
a 7479
7.6%
r 7294
7.4%
l 7116
7.2%
h 7076
7.2%
g 7074
7.2%
Other values (22) 14326
14.5%

georeferenceSources
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

georeferenceRemarks
Text

Missing 

Distinct8
Distinct (%)11.8%
Missing601383
Missing (%)> 99.9%
Memory size4.6 MiB
2025-01-07T10:47:15.782603image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length35
Mean length31.20588235
Min length5

Characters and Unicode

Total characters2122
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.9%

Sample

1st rowGarmin Etrex Vista HCX, Datum WGS84
2nd rowGarmin Etrex Vista HCX, Datum WGS84
3rd rowGarmin Etrex Vista HCX, Datum WGS84
4th rowGarmin Etrex Vista HCX, Datum WGS84
5th rowGarmin Etrex Vista HCX, Datum WGS84
ValueCountFrequency (%)
garmin 54
15.1%
etrex 54
15.1%
vista 54
15.1%
hcx 54
15.1%
datum 54
15.1%
wgs84 54
15.1%
coordinates 7
 
2.0%
camp 7
 
2.0%
for 6
 
1.7%
approximate 2
 
0.6%
Other values (7) 12
 
3.4%
2025-01-07T10:47:15.904006image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2122
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
290
 
13.7%
a 184
 
8.7%
t 175
 
8.2%
r 132
 
6.2%
i 123
 
5.8%
m 118
 
5.6%
G 108
 
5.1%
e 73
 
3.4%
n 67
 
3.2%
s 62
 
2.9%
Other values (24) 790
37.2%

geologicalContextID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

earliestEonOrLowestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

latestEonOrHighestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

earliestEraOrLowestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

latestEraOrHighestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

earliestPeriodOrLowestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

latestPeriodOrHighestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

earliestEpochOrLowestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

latestEpochOrHighestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

earliestAgeOrLowestStage
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

latestAgeOrHighestStage
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

lowestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

highestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

lithostratigraphicTerms
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

group
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

formation
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

member
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

bed
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

identificationID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

verbatimIdentification
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct4
Distinct (%)0.3%
Missing599947
Missing (%)99.7%
Memory size4.6 MiB
2025-01-07T10:47:15.954010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.412234043
Min length3

Characters and Unicode

Total characters12652
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowuncertain
2nd rowuncertain
3rd rowuncertain
4th rowuncertain
5th rowcf.
ValueCountFrequency (%)
uncertain 1355
90.0%
cf 147
 
9.8%
sp 2
 
0.1%
near 2
 
0.1%
2025-01-07T10:47:16.056431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
r 1357
10.7%
e 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
r 1357
10.7%
e 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
r 1357
10.7%
e 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12652
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 2712
21.4%
c 1502
11.9%
r 1357
10.7%
e 1357
10.7%
a 1357
10.7%
t 1355
10.7%
i 1355
10.7%
u 1315
10.4%
. 149
 
1.2%
f 147
 
1.2%
Other values (4) 46
 
0.4%

typeStatus
Text

Missing 

Distinct5
Distinct (%)0.1%
Missing597715
Missing (%)99.4%
Memory size4.6 MiB
2025-01-07T10:47:16.101336image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.176391863
Min length4

Characters and Unicode

Total characters15603
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLECTOTYPE
2nd rowTYPE
3rd rowTYPE
4th rowTYPE
5th rowTYPE
ValueCountFrequency (%)
type 3565
95.4%
syntype 80
 
2.1%
lectotype 67
 
1.8%
neotype 12
 
0.3%
holotype 12
 
0.3%
2025-01-07T10:47:16.199254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3816
24.5%
E 3815
24.5%
T 3803
24.4%
P 3736
23.9%
O 103
 
0.7%
N 92
 
0.6%
S 80
 
0.5%
L 79
 
0.5%
C 67
 
0.4%
H 12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15603
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 3816
24.5%
E 3815
24.5%
T 3803
24.4%
P 3736
23.9%
O 103
 
0.7%
N 92
 
0.6%
S 80
 
0.5%
L 79
 
0.5%
C 67
 
0.4%
H 12
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15603
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 3816
24.5%
E 3815
24.5%
T 3803
24.4%
P 3736
23.9%
O 103
 
0.7%
N 92
 
0.6%
S 80
 
0.5%
L 79
 
0.5%
C 67
 
0.4%
H 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15603
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 3816
24.5%
E 3815
24.5%
T 3803
24.4%
P 3736
23.9%
O 103
 
0.7%
N 92
 
0.6%
S 80
 
0.5%
L 79
 
0.5%
C 67
 
0.4%
H 12
 
0.1%

identifiedBy
Text

Missing 

Distinct95
Distinct (%)1.2%
Missing593267
Missing (%)98.6%
Memory size4.6 MiB
2025-01-07T10:47:16.484499image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length132
Median length124
Mean length94.36840176
Min length10

Characters and Unicode

Total characters772311
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.3%

Sample

1st rowO'Neill, Jennifer K., Fort Hayes State University
2nd rowGardner, Alfred L., Curator (USGS), United States Geological Survey (UNITED STATES)
3rd rowWoodman, Neal, (USGS), United States Geological Survey (UNITED STATES)
4th rowLunde, Darrin P., Collections Manager (MAM), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
5th rowReeder, DeeAnn M., Bucknell University (UNITED STATES)
ValueCountFrequency (%)
united 8033
 
7.9%
states 8033
 
7.9%
of 5420
 
5.3%
museum 5255
 
5.2%
history 5077
 
5.0%
natural 5077
 
5.0%
national 5064
 
5.0%
institution 5007
 
4.9%
smithsonian 5007
 
4.9%
4859
 
4.8%
Other values (272) 44753
44.1%
2025-01-07T10:47:16.762247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 772311
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
93401
 
12.1%
t 49895
 
6.5%
o 47659
 
6.2%
i 45409
 
5.9%
a 41696
 
5.4%
e 39504
 
5.1%
n 38647
 
5.0%
s 36580
 
4.7%
r 29451
 
3.8%
u 25575
 
3.3%
Other values (48) 324494
42.0%

identifiedByID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

dateIdentified
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

identificationReferences
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

identificationVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

identificationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

taxonID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

scientificNameID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

acceptedNameUsageID
Real number (ℝ)

Distinct6815
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4172097.044
Minimum44
Maximum12178528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:16.838523image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile2433176
Q12438019
median2440718
Q35706748
95-th percentile8324617
Maximum12178528
Range12178484
Interquartile range (IQR)3268729

Descriptive statistics

Standard deviation2140042.193
Coefficient of variation (CV)0.5129416144
Kurtosis0.2103153269
Mean4172097.044
Median Absolute Deviation (MAD)8268
Skewness0.9871970609
Sum2.509311939 × 1012
Variance4.579780589 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:16.904600image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2437967 14724
 
2.4%
2440447 11867
 
2.0%
2438904 8874
 
1.5%
2433176 8329
 
1.4%
2438019 7347
 
1.2%
2438655 6840
 
1.1%
2433272 5470
 
0.9%
2439270 5412
 
0.9%
2437782 5206
 
0.9%
4264939 4687
 
0.8%
Other values (6805) 522695
86.9%
ValueCountFrequency (%)
44 1
 
< 0.1%
733 1121
0.2%
734 1
 
< 0.1%
1459 35
 
< 0.1%
5298 1
 
< 0.1%
ValueCountFrequency (%)
12178528 5
 
< 0.1%
11839479 56
 
< 0.1%
11804100 24
 
< 0.1%
11800518 690
0.1%
11693419 4
 
< 0.1%

parentNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

originalNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

nameAccordingToID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

namePublishedInID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

taxonConceptID
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct7326
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:17.104549image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length147
Median length72
Mean length35.02832483
Min length7

Characters and Unicode

Total characters21067821
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique849 ?
Unique (%)0.1%

Sample

1st rowPotos flavus (Schreber, 1774)
2nd rowMicrotus longicaudus longicaudus
3rd rowCarollia brevicaudum (Schinz, 1821)
4th rowPeromyscus mexicanus totontepecus Merriam, 1898
5th rowTursiops truncatus (Montagu, 1821)
ValueCountFrequency (%)
linnaeus 52995
 
2.1%
1758 48641
 
1.9%
thomas 44736
 
1.8%
peromyscus 38753
 
1.5%
merriam 29181
 
1.2%
25993
 
1.0%
rattus 21929
 
0.9%
1821 21801
 
0.9%
microtus 19877
 
0.8%
j.a.allen 18118
 
0.7%
Other values (6496) 2183955
87.1%
2025-01-07T10:47:17.396227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1904528
 
9.0%
s 1657434
 
7.9%
a 1400545
 
6.6%
i 1320831
 
6.3%
e 1211612
 
5.8%
r 1087984
 
5.2%
u 1063056
 
5.0%
o 1056373
 
5.0%
n 919028
 
4.4%
l 817723
 
3.9%
Other values (70) 8628707
41.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21067821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1904528
 
9.0%
s 1657434
 
7.9%
a 1400545
 
6.6%
i 1320831
 
6.3%
e 1211612
 
5.8%
r 1087984
 
5.2%
u 1063056
 
5.0%
o 1056373
 
5.0%
n 919028
 
4.4%
l 817723
 
3.9%
Other values (70) 8628707
41.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21067821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1904528
 
9.0%
s 1657434
 
7.9%
a 1400545
 
6.6%
i 1320831
 
6.3%
e 1211612
 
5.8%
r 1087984
 
5.2%
u 1063056
 
5.0%
o 1056373
 
5.0%
n 919028
 
4.4%
l 817723
 
3.9%
Other values (70) 8628707
41.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21067821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1904528
 
9.0%
s 1657434
 
7.9%
a 1400545
 
6.6%
i 1320831
 
6.3%
e 1211612
 
5.8%
r 1087984
 
5.2%
u 1063056
 
5.0%
o 1056373
 
5.0%
n 919028
 
4.4%
l 817723
 
3.9%
Other values (70) 8628707
41.0%

acceptedNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

parentNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

originalNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

nameAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

namePublishedIn
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

namePublishedInYear
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct253
Distinct (%)< 0.1%
Missing7
Missing (%)< 0.1%
Memory size4.6 MiB
2025-01-07T10:47:17.559811image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length121
Median length113
Mean length90.64064651
Min length11

Characters and Unicode

Total characters54515273
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Carnivora, Caniformia, Procyonidae
2nd rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Rodentia, Myomorpha, Cricetidae, Arvicolinae
3rd rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Chiroptera, Phyllostomidae, Carolliinae
4th rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Rodentia, Myomorpha, Cricetidae, Neotominae
5th rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Cetacea, Odontoceti, Delphinidae
ValueCountFrequency (%)
vertebrata 601442
11.9%
animalia 601442
11.9%
chordata 601442
11.9%
mammalia 601441
11.9%
eutheria 593341
11.7%
rodentia 297636
 
5.9%
myomorpha 209417
 
4.1%
chiroptera 129086
 
2.5%
cricetidae 107243
 
2.1%
muridae 93911
 
1.9%
Other values (328) 1234181
24.3%
2025-01-07T10:47:17.800342image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 54515273
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 8383067
15.4%
i 4797600
 
8.8%
, 4469138
 
8.2%
4469138
 
8.2%
e 4068524
 
7.5%
r 4037606
 
7.4%
t 3533330
 
6.5%
o 2704288
 
5.0%
m 2453478
 
4.5%
h 1861673
 
3.4%
Other values (38) 13737431
25.2%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:17.851444image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4811608
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 601451
100.0%
2025-01-07T10:47:17.943045image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1202902
25.0%
i 1202902
25.0%
n 601451
12.5%
A 601451
12.5%
m 601451
12.5%
l 601451
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1202902
25.0%
i 1202902
25.0%
n 601451
12.5%
A 601451
12.5%
m 601451
12.5%
l 601451
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1202902
25.0%
i 1202902
25.0%
n 601451
12.5%
A 601451
12.5%
m 601451
12.5%
l 601451
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1202902
25.0%
i 1202902
25.0%
n 601451
12.5%
A 601451
12.5%
m 601451
12.5%
l 601451
12.5%

phylum
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:17.984289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4811608
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 601449
> 99.9%
mollusca 2
 
< 0.1%
2025-01-07T10:47:18.079512image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1202900
25.0%
o 601451
12.5%
h 601449
12.5%
C 601449
12.5%
r 601449
12.5%
d 601449
12.5%
t 601449
12.5%
l 4
 
< 0.1%
M 2
 
< 0.1%
u 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1202900
25.0%
o 601451
12.5%
h 601449
12.5%
C 601449
12.5%
r 601449
12.5%
d 601449
12.5%
t 601449
12.5%
l 4
 
< 0.1%
M 2
 
< 0.1%
u 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1202900
25.0%
o 601451
12.5%
h 601449
12.5%
C 601449
12.5%
r 601449
12.5%
d 601449
12.5%
t 601449
12.5%
l 4
 
< 0.1%
M 2
 
< 0.1%
u 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811608
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1202900
25.0%
o 601451
12.5%
h 601449
12.5%
C 601449
12.5%
r 601449
12.5%
d 601449
12.5%
t 601449
12.5%
l 4
 
< 0.1%
M 2
 
< 0.1%
u 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

class
Text

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size4.6 MiB
2025-01-07T10:47:18.123511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.000006651
Min length8

Characters and Unicode

Total characters4811604
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMammalia
2nd rowMammalia
3rd rowMammalia
4th rowMammalia
5th rowMammalia
ValueCountFrequency (%)
mammalia 601448
> 99.9%
gastropoda 2
 
< 0.1%
2025-01-07T10:47:18.229892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1804348
37.5%
m 1202896
25.0%
M 601448
 
12.5%
l 601448
 
12.5%
i 601448
 
12.5%
o 4
 
< 0.1%
s 2
 
< 0.1%
G 2
 
< 0.1%
t 2
 
< 0.1%
r 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4811604
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1804348
37.5%
m 1202896
25.0%
M 601448
 
12.5%
l 601448
 
12.5%
i 601448
 
12.5%
o 4
 
< 0.1%
s 2
 
< 0.1%
G 2
 
< 0.1%
t 2
 
< 0.1%
r 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4811604
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1804348
37.5%
m 1202896
25.0%
M 601448
 
12.5%
l 601448
 
12.5%
i 601448
 
12.5%
o 4
 
< 0.1%
s 2
 
< 0.1%
G 2
 
< 0.1%
t 2
 
< 0.1%
r 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4811604
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1804348
37.5%
m 1202896
25.0%
M 601448
 
12.5%
l 601448
 
12.5%
i 601448
 
12.5%
o 4
 
< 0.1%
s 2
 
< 0.1%
G 2
 
< 0.1%
t 2
 
< 0.1%
r 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

order
Text

Distinct29
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size4.6 MiB
2025-01-07T10:47:18.291013image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length8
Mean length8.868951264
Min length6

Characters and Unicode

Total characters5334213
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCarnivora
2nd rowRodentia
3rd rowChiroptera
4th rowRodentia
5th rowCetacea
ValueCountFrequency (%)
rodentia 297636
49.5%
chiroptera 129084
21.5%
cetacea 47588
 
7.9%
carnivora 47294
 
7.9%
soricomorpha 30383
 
5.1%
lagomorpha 11977
 
2.0%
artiodactyla 11375
 
1.9%
primates 10781
 
1.8%
didelphimorphia 5645
 
0.9%
diprotodontia 1652
 
0.3%
Other values (19) 8033
 
1.3%
2025-01-07T10:47:18.414200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 725656
13.6%
o 618974
11.6%
i 555654
10.4%
e 546103
10.2%
t 514236
9.6%
r 462546
8.7%
n 351518
6.6%
d 320914
6.0%
R 297636
5.6%
C 224385
 
4.2%
Other values (22) 716591
13.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5334213
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 725656
13.6%
o 618974
11.6%
i 555654
10.4%
e 546103
10.2%
t 514236
9.6%
r 462546
8.7%
n 351518
6.6%
d 320914
6.0%
R 297636
5.6%
C 224385
 
4.2%
Other values (22) 716591
13.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5334213
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 725656
13.6%
o 618974
11.6%
i 555654
10.4%
e 546103
10.2%
t 514236
9.6%
r 462546
8.7%
n 351518
6.6%
d 320914
6.0%
R 297636
5.6%
C 224385
 
4.2%
Other values (22) 716591
13.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5334213
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 725656
13.6%
o 618974
11.6%
i 555654
10.4%
e 546103
10.2%
t 514236
9.6%
r 462546
8.7%
n 351518
6.6%
d 320914
6.0%
R 297636
5.6%
C 224385
 
4.2%
Other values (22) 716591
13.4%

superfamily
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

family
Text

Distinct158
Distinct (%)< 0.1%
Missing1158
Missing (%)0.2%
Memory size4.6 MiB
2025-01-07T10:47:18.574027image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.24363436
Min length6

Characters and Unicode

Total characters6149182
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowProcyonidae
2nd rowCricetidae
3rd rowPhyllostomidae
4th rowCricetidae
5th rowDelphinidae
ValueCountFrequency (%)
cricetidae 107243
17.9%
muridae 93911
15.6%
phyllostomidae 55530
 
9.3%
sciuridae 46130
 
7.7%
soricidae 27470
 
4.6%
delphinidae 23642
 
3.9%
vespertilionidae 22260
 
3.7%
heteromyidae 19997
 
3.3%
molossidae 13560
 
2.3%
canidae 12559
 
2.1%
Other values (148) 177991
29.7%
2025-01-07T10:47:18.807883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 944314
15.4%
i 915778
14.9%
a 664057
10.8%
d 635413
10.3%
r 412407
 
6.7%
o 362011
 
5.9%
t 276360
 
4.5%
l 229210
 
3.7%
c 221440
 
3.6%
u 159982
 
2.6%
Other values (32) 1328210
21.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6149182
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 944314
15.4%
i 915778
14.9%
a 664057
10.8%
d 635413
10.3%
r 412407
 
6.7%
o 362011
 
5.9%
t 276360
 
4.5%
l 229210
 
3.7%
c 221440
 
3.6%
u 159982
 
2.6%
Other values (32) 1328210
21.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6149182
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 944314
15.4%
i 915778
14.9%
a 664057
10.8%
d 635413
10.3%
r 412407
 
6.7%
o 362011
 
5.9%
t 276360
 
4.5%
l 229210
 
3.7%
c 221440
 
3.6%
u 159982
 
2.6%
Other values (32) 1328210
21.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6149182
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 944314
15.4%
i 915778
14.9%
a 664057
10.8%
d 635413
10.3%
r 412407
 
6.7%
o 362011
 
5.9%
t 276360
 
4.5%
l 229210
 
3.7%
c 221440
 
3.6%
u 159982
 
2.6%
Other values (32) 1328210
21.6%

subfamily
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

tribe
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

subtribe
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

genus
Text

Distinct1129
Distinct (%)0.2%
Missing1999
Missing (%)0.3%
Memory size4.6 MiB
2025-01-07T10:47:19.014031image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.505269813
Min length2

Characters and Unicode

Total characters5098501
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)< 0.1%

Sample

1st rowPotos
2nd rowMicrotus
3rd rowCarollia
4th rowPeromyscus
5th rowTursiops
ValueCountFrequency (%)
peromyscus 38753
 
6.5%
microtus 19877
 
3.3%
rattus 16463
 
2.7%
sorex 15826
 
2.6%
artibeus 12467
 
2.1%
carollia 12281
 
2.0%
tursiops 11894
 
2.0%
tamias 11871
 
2.0%
mastomys 11447
 
1.9%
mus 10554
 
1.8%
Other values (1119) 438019
73.1%
2025-01-07T10:47:19.283016image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 603875
 
11.8%
o 509579
 
10.0%
a 348715
 
6.8%
r 348305
 
6.8%
u 337607
 
6.6%
i 326618
 
6.4%
e 313769
 
6.2%
t 248513
 
4.9%
l 221347
 
4.3%
y 216014
 
4.2%
Other values (40) 1624159
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5098501
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 603875
 
11.8%
o 509579
 
10.0%
a 348715
 
6.8%
r 348305
 
6.8%
u 337607
 
6.6%
i 326618
 
6.4%
e 313769
 
6.2%
t 248513
 
4.9%
l 221347
 
4.3%
y 216014
 
4.2%
Other values (40) 1624159
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5098501
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 603875
 
11.8%
o 509579
 
10.0%
a 348715
 
6.8%
r 348305
 
6.8%
u 337607
 
6.6%
i 326618
 
6.4%
e 313769
 
6.2%
t 248513
 
4.9%
l 221347
 
4.3%
y 216014
 
4.2%
Other values (40) 1624159
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5098501
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 603875
 
11.8%
o 509579
 
10.0%
a 348715
 
6.8%
r 348305
 
6.8%
u 337607
 
6.6%
i 326618
 
6.4%
e 313769
 
6.2%
t 248513
 
4.9%
l 221347
 
4.3%
y 216014
 
4.2%
Other values (40) 1624159
31.9%
Distinct1115
Distinct (%)0.2%
Missing2002
Missing (%)0.3%
Memory size4.6 MiB
2025-01-07T10:47:19.494348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.504708491
Min length2

Characters and Unicode

Total characters5098139
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)< 0.1%

Sample

1st rowPotos
2nd rowMicrotus
3rd rowCarollia
4th rowPeromyscus
5th rowTursiops
ValueCountFrequency (%)
peromyscus 38753
 
6.5%
microtus 19877
 
3.3%
rattus 16463
 
2.7%
sorex 15826
 
2.6%
artibeus 12470
 
2.1%
carollia 12281
 
2.0%
tursiops 11894
 
2.0%
tamias 11871
 
2.0%
mastomys 11447
 
1.9%
mus 10554
 
1.8%
Other values (1105) 438013
73.1%
2025-01-07T10:47:19.771739image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 603400
 
11.8%
o 512945
 
10.1%
r 348628
 
6.8%
a 347937
 
6.8%
u 335989
 
6.6%
i 330068
 
6.5%
e 312892
 
6.1%
t 245783
 
4.8%
l 219644
 
4.3%
m 215952
 
4.2%
Other values (40) 1624901
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5098139
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 603400
 
11.8%
o 512945
 
10.1%
r 348628
 
6.8%
a 347937
 
6.8%
u 335989
 
6.6%
i 330068
 
6.5%
e 312892
 
6.1%
t 245783
 
4.8%
l 219644
 
4.3%
m 215952
 
4.2%
Other values (40) 1624901
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5098139
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 603400
 
11.8%
o 512945
 
10.1%
r 348628
 
6.8%
a 347937
 
6.8%
u 335989
 
6.6%
i 330068
 
6.5%
e 312892
 
6.1%
t 245783
 
4.8%
l 219644
 
4.3%
m 215952
 
4.2%
Other values (40) 1624901
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5098139
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 603400
 
11.8%
o 512945
 
10.1%
r 348628
 
6.8%
a 347937
 
6.8%
u 335989
 
6.6%
i 330068
 
6.5%
e 312892
 
6.1%
t 245783
 
4.8%
l 219644
 
4.3%
m 215952
 
4.2%
Other values (40) 1624901
31.9%

subgenus
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

infragenericEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

specificEpithet
Text

Missing 

Distinct2771
Distinct (%)0.5%
Missing29657
Missing (%)4.9%
Memory size4.6 MiB
2025-01-07T10:47:19.989813image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.673424345
Min length2

Characters and Unicode

Total characters4959412
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)< 0.1%

Sample

1st rowflavus
2nd rowlongicaudus
3rd rowbrevicaudum
4th rowmexicanus
5th rowtruncatus
ValueCountFrequency (%)
maniculatus 15647
 
2.7%
truncatus 11873
 
2.1%
musculus 8519
 
1.5%
perspicillata 8339
 
1.5%
leucopus 7382
 
1.3%
pennsylvanicus 6799
 
1.2%
jamaicensis 5581
 
1.0%
brevicauda 5546
 
1.0%
rattus 5466
 
1.0%
cinereus 4761
 
0.8%
Other values (2761) 491881
86.0%
2025-01-07T10:47:20.274874image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 572805
11.5%
i 552816
11.1%
a 502230
10.1%
u 462190
9.3%
e 328983
 
6.6%
r 327562
 
6.6%
n 325551
 
6.6%
l 286376
 
5.8%
t 270290
 
5.5%
c 258935
 
5.2%
Other values (16) 1071674
21.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4959412
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 572805
11.5%
i 552816
11.1%
a 502230
10.1%
u 462190
9.3%
e 328983
 
6.6%
r 327562
 
6.6%
n 325551
 
6.6%
l 286376
 
5.8%
t 270290
 
5.5%
c 258935
 
5.2%
Other values (16) 1071674
21.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4959412
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 572805
11.5%
i 552816
11.1%
a 502230
10.1%
u 462190
9.3%
e 328983
 
6.6%
r 327562
 
6.6%
n 325551
 
6.6%
l 286376
 
5.8%
t 270290
 
5.5%
c 258935
 
5.2%
Other values (16) 1071674
21.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4959412
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 572805
11.5%
i 552816
11.1%
a 502230
10.1%
u 462190
9.3%
e 328983
 
6.6%
r 327562
 
6.6%
n 325551
 
6.6%
l 286376
 
5.8%
t 270290
 
5.5%
c 258935
 
5.2%
Other values (16) 1071674
21.6%

infraspecificEpithet
Text

Missing 

Distinct2443
Distinct (%)1.1%
Missing386527
Missing (%)64.3%
Memory size4.6 MiB
2025-01-07T10:47:20.468355image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.768327409
Min length3

Characters and Unicode

Total characters1884524
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique226 ?
Unique (%)0.1%

Sample

1st rowlongicaudus
2nd rowtotontepecus
3rd rowmarinensis
4th rowbairdii
5th rowmerriami
ValueCountFrequency (%)
domesticus 4357
 
2.0%
pennsylvanicus 4127
 
1.9%
talpoides 3712
 
1.7%
cinereus 3602
 
1.7%
trowbridgii 2145
 
1.0%
merriami 2051
 
1.0%
lestes 1946
 
0.9%
panamensis 1556
 
0.7%
personatus 1522
 
0.7%
mexicana 1479
 
0.7%
Other values (2433) 188427
87.7%
2025-01-07T10:47:20.812247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 232184
12.3%
i 220508
11.7%
a 170831
9.1%
e 153788
 
8.2%
n 142641
 
7.6%
u 141648
 
7.5%
r 121518
 
6.4%
o 101734
 
5.4%
l 100611
 
5.3%
c 89089
 
4.7%
Other values (16) 409972
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1884524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 232184
12.3%
i 220508
11.7%
a 170831
9.1%
e 153788
 
8.2%
n 142641
 
7.6%
u 141648
 
7.5%
r 121518
 
6.4%
o 101734
 
5.4%
l 100611
 
5.3%
c 89089
 
4.7%
Other values (16) 409972
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1884524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 232184
12.3%
i 220508
11.7%
a 170831
9.1%
e 153788
 
8.2%
n 142641
 
7.6%
u 141648
 
7.5%
r 121518
 
6.4%
o 101734
 
5.4%
l 100611
 
5.3%
c 89089
 
4.7%
Other values (16) 409972
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1884524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 232184
12.3%
i 220508
11.7%
a 170831
9.1%
e 153788
 
8.2%
n 142641
 
7.6%
u 141648
 
7.5%
r 121518
 
6.4%
o 101734
 
5.4%
l 100611
 
5.3%
c 89089
 
4.7%
Other values (16) 409972
21.8%

cultivarEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:20.869756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.974819229
Min length5

Characters and Unicode

Total characters4796463
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowSPECIES
2nd rowSUBSPECIES
3rd rowSPECIES
4th rowSUBSPECIES
5th rowSPECIES
ValueCountFrequency (%)
species 356873
59.3%
subspecies 214924
35.7%
genus 27655
 
4.6%
order 1157
 
0.2%
family 841
 
0.1%
phylum 1
 
< 0.1%
2025-01-07T10:47:20.970545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1386173
28.9%
E 1172406
24.4%
I 572638
11.9%
P 571798
11.9%
C 571797
11.9%
U 242580
 
5.1%
B 214924
 
4.5%
G 27655
 
0.6%
N 27655
 
0.6%
R 2314
 
< 0.1%
Other values (8) 6523
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4796463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1386173
28.9%
E 1172406
24.4%
I 572638
11.9%
P 571798
11.9%
C 571797
11.9%
U 242580
 
5.1%
B 214924
 
4.5%
G 27655
 
0.6%
N 27655
 
0.6%
R 2314
 
< 0.1%
Other values (8) 6523
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4796463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1386173
28.9%
E 1172406
24.4%
I 572638
11.9%
P 571798
11.9%
C 571797
11.9%
U 242580
 
5.1%
B 214924
 
4.5%
G 27655
 
0.6%
N 27655
 
0.6%
R 2314
 
< 0.1%
Other values (8) 6523
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4796463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1386173
28.9%
E 1172406
24.4%
I 572638
11.9%
P 571798
11.9%
C 571797
11.9%
U 242580
 
5.1%
B 214924
 
4.5%
G 27655
 
0.6%
N 27655
 
0.6%
R 2314
 
< 0.1%
Other values (8) 6523
 
0.1%

verbatimTaxonRank
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

vernacularName
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

nomenclaturalCode
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:21.014164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.919303484
Min length7

Characters and Unicode

Total characters4763073
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACCEPTED
2nd rowSYNONYM
3rd rowACCEPTED
4th rowSYNONYM
5th rowACCEPTED
ValueCountFrequency (%)
accepted 552476
91.9%
synonym 48535
 
8.1%
doubtful 440
 
0.1%
2025-01-07T10:47:21.106319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1104952
23.2%
E 1104952
23.2%
T 552916
11.6%
D 552916
11.6%
A 552476
11.6%
P 552476
11.6%
Y 97070
 
2.0%
N 97070
 
2.0%
O 48975
 
1.0%
S 48535
 
1.0%
Other values (5) 50735
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4763073
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1104952
23.2%
E 1104952
23.2%
T 552916
11.6%
D 552916
11.6%
A 552476
11.6%
P 552476
11.6%
Y 97070
 
2.0%
N 97070
 
2.0%
O 48975
 
1.0%
S 48535
 
1.0%
Other values (5) 50735
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4763073
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1104952
23.2%
E 1104952
23.2%
T 552916
11.6%
D 552916
11.6%
A 552476
11.6%
P 552476
11.6%
Y 97070
 
2.0%
N 97070
 
2.0%
O 48975
 
1.0%
S 48535
 
1.0%
Other values (5) 50735
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4763073
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1104952
23.2%
E 1104952
23.2%
T 552916
11.6%
D 552916
11.6%
A 552476
11.6%
P 552476
11.6%
Y 97070
 
2.0%
N 97070
 
2.0%
O 48975
 
1.0%
S 48535
 
1.0%
Other values (5) 50735
 
1.1%

nomenclaturalStatus
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

taxonRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

datasetKey
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:21.162321image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters21652236
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row821cc27a-e3bb-4bc5-ac34-89ada245069d
2nd row821cc27a-e3bb-4bc5-ac34-89ada245069d
3rd row821cc27a-e3bb-4bc5-ac34-89ada245069d
4th row821cc27a-e3bb-4bc5-ac34-89ada245069d
5th row821cc27a-e3bb-4bc5-ac34-89ada245069d
ValueCountFrequency (%)
821cc27a-e3bb-4bc5-ac34-89ada245069d 601451
100.0%
2025-01-07T10:47:21.271686image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 2405804
11.1%
a 2405804
11.1%
- 2405804
11.1%
2 1804353
8.3%
4 1804353
8.3%
b 1804353
8.3%
8 1202902
 
5.6%
3 1202902
 
5.6%
9 1202902
 
5.6%
d 1202902
 
5.6%
Other values (6) 4210157
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21652236
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 2405804
11.1%
a 2405804
11.1%
- 2405804
11.1%
2 1804353
8.3%
4 1804353
8.3%
b 1804353
8.3%
8 1202902
 
5.6%
3 1202902
 
5.6%
9 1202902
 
5.6%
d 1202902
 
5.6%
Other values (6) 4210157
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21652236
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 2405804
11.1%
a 2405804
11.1%
- 2405804
11.1%
2 1804353
8.3%
4 1804353
8.3%
b 1804353
8.3%
8 1202902
 
5.6%
3 1202902
 
5.6%
9 1202902
 
5.6%
d 1202902
 
5.6%
Other values (6) 4210157
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21652236
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 2405804
11.1%
a 2405804
11.1%
- 2405804
11.1%
2 1804353
8.3%
4 1804353
8.3%
b 1804353
8.3%
8 1202902
 
5.6%
3 1202902
 
5.6%
9 1202902
 
5.6%
d 1202902
 
5.6%
Other values (6) 4210157
19.4%

publishingCountry
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:21.314232image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1202902
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 601451
100.0%
2025-01-07T10:47:21.405461image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 601451
50.0%
S 601451
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1202902
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 601451
50.0%
S 601451
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1202902
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 601451
50.0%
S 601451
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1202902
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 601451
50.0%
S 601451
50.0%
Distinct185984
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:21.551815image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99573698
Min length20

Characters and Unicode

Total characters14432260
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38937 ?
Unique (%)6.5%

Sample

1st row2024-12-02T13:58:01.255Z
2nd row2024-12-02T13:59:38.442Z
3rd row2024-12-02T13:56:07.605Z
4th row2024-12-02T13:58:24.850Z
5th row2024-12-02T13:56:12.476Z
ValueCountFrequency (%)
2024-12-02t13:57:24.313z 17
 
< 0.1%
2024-12-02t13:57:59.063z 17
 
< 0.1%
2024-12-02t13:57:52.813z 17
 
< 0.1%
2024-12-02t13:57:14.377z 17
 
< 0.1%
2024-12-02t13:57:15.231z 17
 
< 0.1%
2024-12-02t13:57:52.024z 16
 
< 0.1%
2024-12-02t13:57:50.062z 16
 
< 0.1%
2024-12-02t13:57:25.776z 16
 
< 0.1%
2024-12-02t13:56:59.760z 15
 
< 0.1%
2024-12-02t13:57:42.979z 15
 
< 0.1%
Other values (185974) 601288
> 99.9%
2025-01-07T10:47:21.778261image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

elevation
Real number (ℝ)

Missing 

Distinct1569
Distinct (%)1.5%
Missing496901
Missing (%)82.6%
Infinite0
Infinite (%)0.0%
Mean1115.120238
Minimum-94
Maximum6400
Zeros138
Zeros (%)< 0.1%
Negative7
Negative (%)< 0.1%
Memory size4.6 MiB
2025-01-07T10:47:21.852213image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-94
5-th percentile23
Q1183
median975
Q31753
95-th percentile2972
Maximum6400
Range6494
Interquartile range (IQR)1570

Descriptive statistics

Standard deviation962.3856314
Coefficient of variation (CV)0.86303306
Kurtosis-0.1604923074
Mean1115.120238
Median Absolute Deviation (MAD)792
Skewness0.7594560225
Sum116585820.9
Variance926186.1036
MonotonicityNot monotonic
2025-01-07T10:47:21.913094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
155 2555
 
0.4%
150 2080
 
0.3%
975 1931
 
0.3%
1829 1920
 
0.3%
1219 1756
 
0.3%
1524 1715
 
0.3%
2438 1448
 
0.2%
2134 1349
 
0.2%
914 1245
 
0.2%
610 1175
 
0.2%
Other values (1559) 87376
 
14.5%
(Missing) 496901
82.6%
ValueCountFrequency (%)
-94 1
 
< 0.1%
-55 1
 
< 0.1%
-53 5
 
< 0.1%
0 138
< 0.1%
0.5 2
 
< 0.1%
ValueCountFrequency (%)
6400 2
 
< 0.1%
5486 1
 
< 0.1%
5334 1
 
< 0.1%
5182 14
< 0.1%
5029 4
 
< 0.1%

elevationAccuracy
Real number (ℝ)

Missing 

Distinct72
Distinct (%)1.9%
Missing597572
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean101.1990204
Minimum0
Maximum1500
Zeros7
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:21.972973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q138
median46
Q3150
95-th percentile304.5
Maximum1500
Range1500
Interquartile range (IQR)112

Descriptive statistics

Standard deviation101.9062431
Coefficient of variation (CV)1.006988434
Kurtosis13.26843338
Mean101.1990204
Median Absolute Deviation (MAD)31
Skewness2.267754595
Sum392551
Variance10384.88238
MonotonicityNot monotonic
2025-01-07T10:47:22.035646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 907
 
0.2%
150 345
 
0.1%
250 244
 
< 0.1%
304.5 236
 
< 0.1%
120 156
 
< 0.1%
46 152
 
< 0.1%
76.5 149
 
< 0.1%
100 145
 
< 0.1%
15 122
 
< 0.1%
37.5 108
 
< 0.1%
Other values (62) 1315
 
0.2%
(Missing) 597572
99.4%
ValueCountFrequency (%)
0 7
 
< 0.1%
0.5 1
 
< 0.1%
1 8
 
< 0.1%
1.5 27
< 0.1%
3 20
< 0.1%
ValueCountFrequency (%)
1500 1
< 0.1%
1000 1
< 0.1%
914.5 1
< 0.1%
823 1
< 0.1%
762 1
< 0.1%

depth
Real number (ℝ)

Missing 

Distinct2
Distinct (%)66.7%
Missing601448
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1351
Minimum853
Maximum1600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:22.085916image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum853
5-th percentile927.7
Q11226.5
median1600
Q31600
95-th percentile1600
Maximum1600
Range747
Interquartile range (IQR)373.5

Descriptive statistics

Standard deviation431.2806511
Coefficient of variation (CV)0.3192306818
Kurtosisnan
Mean1351
Median Absolute Deviation (MAD)0
Skewness-1.732050808
Sum4053
Variance186003
MonotonicityIncreasing
2025-01-07T10:47:22.131429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1600 2
 
< 0.1%
853 1
 
< 0.1%
(Missing) 601448
> 99.9%
ValueCountFrequency (%)
853 1
< 0.1%
1600 2
< 0.1%
ValueCountFrequency (%)
1600 2
< 0.1%
853 1
< 0.1%

depthAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

distanceFromCentroidInMeters
Real number (ℝ)

Missing 

Distinct34
Distinct (%)12.5%
Missing601180
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean2478.885301
Minimum0
Maximum4684.640708
Zeros16
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:22.183659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1918.1358065
median1895.275346
Q34411.160071
95-th percentile4411.160071
Maximum4684.640708
Range4684.640708
Interquartile range (IQR)3493.024265

Descriptive statistics

Standard deviation1676.589797
Coefficient of variation (CV)0.6763482748
Kurtosis-1.732127993
Mean2478.885301
Median Absolute Deviation (MAD)1077.154244
Skewness0.1017334534
Sum671777.9167
Variance2810953.348
MonotonicityNot monotonic
2025-01-07T10:47:22.236617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4411.160071 100
 
< 0.1%
918.1358065 59
 
< 0.1%
818.121102 23
 
< 0.1%
0 16
 
< 0.1%
1698.881357 14
 
< 0.1%
1895.275346 9
 
< 0.1%
2501.879816 7
 
< 0.1%
1136.480246 5
 
< 0.1%
862.8264354 5
 
< 0.1%
3374.389196 4
 
< 0.1%
Other values (24) 29
 
< 0.1%
(Missing) 601180
> 99.9%
ValueCountFrequency (%)
0 16
< 0.1%
365.7761464 1
 
< 0.1%
438.7371189 1
 
< 0.1%
801.5718428 1
 
< 0.1%
818.121102 23
< 0.1%
ValueCountFrequency (%)
4684.640708 1
 
< 0.1%
4610.975198 1
 
< 0.1%
4411.160071 100
< 0.1%
4406.152374 1
 
< 0.1%
4226.709834 1
 
< 0.1%

issue
Text

Distinct117
Distinct (%)< 0.1%
Missing13
Missing (%)< 0.1%
Memory size4.6 MiB
2025-01-07T10:47:22.287359image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length187
Median length48
Mean length62.38084724
Min length48

Characters and Unicode

Total characters37518212
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)< 0.1%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
3rd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;TAXON_MATCH_FUZZY
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
5th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES;CONTINENT_INVALID
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count 356968
59.4%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 110523
 
18.4%
occurrence_status_inferred_from_individual_count;taxon_match_higherrank 68486
 
11.4%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 19137
 
3.2%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;continent_invalid 9426
 
1.6%
occurrence_status_inferred_from_individual_count;taxon_match_fuzzy 7808
 
1.3%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;geodetic_datum_invalid 6304
 
1.0%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;taxon_match_higherrank 3860
 
0.6%
occurrence_status_inferred_from_individual_count;country_derived_from_coordinates;geodetic_datum_assumed_wgs84;continent_invalid 3671
 
0.6%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_invalid 3605
 
0.6%
Other values (107) 11650
 
1.9%
2025-01-07T10:47:22.431450image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 3814538
10.2%
R 3273760
 
8.7%
E 3131386
 
8.3%
I 2892193
 
7.7%
N 2889124
 
7.7%
C 2776336
 
7.4%
U 2757004
 
7.3%
T 2507326
 
6.7%
D 2429693
 
6.5%
O 2238112
 
6.0%
Other values (18) 8808740
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37518212
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 3814538
10.2%
R 3273760
 
8.7%
E 3131386
 
8.3%
I 2892193
 
7.7%
N 2889124
 
7.7%
C 2776336
 
7.4%
U 2757004
 
7.3%
T 2507326
 
6.7%
D 2429693
 
6.5%
O 2238112
 
6.0%
Other values (18) 8808740
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37518212
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 3814538
10.2%
R 3273760
 
8.7%
E 3131386
 
8.3%
I 2892193
 
7.7%
N 2889124
 
7.7%
C 2776336
 
7.4%
U 2757004
 
7.3%
T 2507326
 
6.7%
D 2429693
 
6.5%
O 2238112
 
6.0%
Other values (18) 8808740
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37518212
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 3814538
10.2%
R 3273760
 
8.7%
E 3131386
 
8.3%
I 2892193
 
7.7%
N 2889124
 
7.7%
C 2776336
 
7.4%
U 2757004
 
7.3%
T 2507326
 
6.7%
D 2429693
 
6.5%
O 2238112
 
6.0%
Other values (18) 8808740
23.5%

mediaType
Text

Missing 

Distinct55
Distinct (%)< 0.1%
Missing45831
Missing (%)7.6%
Memory size4.6 MiB
2025-01-07T10:47:22.489528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1385
Median length10
Mean length11.66078975
Min length10

Characters and Unicode

Total characters6478968
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowStillImage
2nd rowStillImage
3rd rowStillImage
4th rowStillImage
5th rowStillImage
ValueCountFrequency (%)
stillimage 509092
91.6%
stillimage;stillimage 38794
 
7.0%
stillimage;stillimage;stillimage 2854
 
0.5%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 1339
 
0.2%
stillimage;stillimage;stillimage;stillimage 1231
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 614
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage 321
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 256
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 250
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 170
 
< 0.1%
Other values (45) 699
 
0.1%
2025-01-07T10:47:22.626526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1279016
19.7%
S 639508
9.9%
t 639508
9.9%
i 639508
9.9%
I 639508
9.9%
m 639508
9.9%
a 639508
9.9%
g 639508
9.9%
e 639508
9.9%
; 83888
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6478968
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1279016
19.7%
S 639508
9.9%
t 639508
9.9%
i 639508
9.9%
I 639508
9.9%
m 639508
9.9%
a 639508
9.9%
g 639508
9.9%
e 639508
9.9%
; 83888
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6478968
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1279016
19.7%
S 639508
9.9%
t 639508
9.9%
i 639508
9.9%
I 639508
9.9%
m 639508
9.9%
a 639508
9.9%
g 639508
9.9%
e 639508
9.9%
; 83888
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6478968
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1279016
19.7%
S 639508
9.9%
t 639508
9.9%
i 639508
9.9%
I 639508
9.9%
m 639508
9.9%
a 639508
9.9%
g 639508
9.9%
e 639508
9.9%
; 83888
 
1.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size587.5 KiB
False
447917 
True
153534 
ValueCountFrequency (%)
False 447917
74.5%
True 153534
 
25.5%
2025-01-07T10:47:22.684723image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hasGeospatialIssues
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size587.5 KiB
False
599368 
True
 
2083
ValueCountFrequency (%)
False 599368
99.7%
True 2083
 
0.3%
2025-01-07T10:47:22.724722image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

taxonKey
Real number (ℝ)

Distinct7326
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4297332.295
Minimum44
Maximum12178528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:22.775886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile2433176
Q12438038
median4263305
Q35707326
95-th percentile8749445
Maximum12178528
Range12178484
Interquartile range (IQR)3269288

Descriptive statistics

Standard deviation2120343.576
Coefficient of variation (CV)0.4934092666
Kurtosis-0.350811812
Mean4297332.295
Median Absolute Deviation (MAD)1825129
Skewness0.780442393
Sum2.584634806 × 1012
Variance4.49585688 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:22.839884image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2437967 13357
 
2.2%
2440447 11847
 
2.0%
2438904 8874
 
1.5%
2433176 8329
 
1.4%
2438019 7116
 
1.2%
2433272 5470
 
0.9%
2439270 5412
 
0.9%
2437782 5206
 
0.9%
4264939 4687
 
0.8%
5706760 4437
 
0.7%
Other values (7316) 526716
87.6%
ValueCountFrequency (%)
44 1
 
< 0.1%
733 1121
0.2%
734 1
 
< 0.1%
1459 35
 
< 0.1%
5298 1
 
< 0.1%
ValueCountFrequency (%)
12178528 5
 
< 0.1%
12167959 11
 
< 0.1%
12149424 6
 
< 0.1%
11804100 24
 
< 0.1%
11800518 690
0.1%

acceptedTaxonKey
Real number (ℝ)

Distinct6815
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4172097.044
Minimum44
Maximum12178528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:22.979510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile2433176
Q12438019
median2440718
Q35706748
95-th percentile8324617
Maximum12178528
Range12178484
Interquartile range (IQR)3268729

Descriptive statistics

Standard deviation2140042.193
Coefficient of variation (CV)0.5129416144
Kurtosis0.2103153269
Mean4172097.044
Median Absolute Deviation (MAD)8268
Skewness0.9871970609
Sum2.509311939 × 1012
Variance4.579780589 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:23.044510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2437967 14724
 
2.4%
2440447 11867
 
2.0%
2438904 8874
 
1.5%
2433176 8329
 
1.4%
2438019 7347
 
1.2%
2438655 6840
 
1.1%
2433272 5470
 
0.9%
2439270 5412
 
0.9%
2437782 5206
 
0.9%
4264939 4687
 
0.8%
Other values (6805) 522695
86.9%
ValueCountFrequency (%)
44 1
 
< 0.1%
733 1121
0.2%
734 1
 
< 0.1%
1459 35
 
< 0.1%
5298 1
 
< 0.1%
ValueCountFrequency (%)
12178528 5
 
< 0.1%
11839479 56
 
< 0.1%
11804100 24
 
< 0.1%
11800518 690
0.1%
11693419 4
 
< 0.1%

kingdomKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.095423image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum601451
Variance0
MonotonicityIncreasing
2025-01-07T10:47:23.137375image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 601451
100.0%
ValueCountFrequency (%)
1 601451
100.0%
ValueCountFrequency (%)
1 601451
100.0%

phylumKey
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.0000266
Minimum44
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.179578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile44
Q144
median44
Q344
95-th percentile44
Maximum52
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0145882937
Coefficient of variation (CV)0.000331551929
Kurtosis300723
Mean44.0000266
Median Absolute Deviation (MAD)0
Skewness548.3830778
Sum26463860
Variance0.000212818313
MonotonicityNot monotonic
2025-01-07T10:47:23.227579image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
44 601449
> 99.9%
52 2
 
< 0.1%
ValueCountFrequency (%)
44 601449
> 99.9%
52 2
 
< 0.1%
ValueCountFrequency (%)
52 2
 
< 0.1%
44 601449
> 99.9%

classKey
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean358.9995544
Minimum225
Maximum359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.274088image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum225
5-th percentile359
Q1359
median359
Q3359
95-th percentile359
Maximum359
Range134
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2443541226
Coefficient of variation (CV)0.0006806529968
Kurtosis300722.5
Mean358.9995544
Median Absolute Deviation (MAD)0
Skewness-548.3826219
Sum215920282
Variance0.05970893722
MonotonicityNot monotonic
2025-01-07T10:47:23.322682image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
359 601448
> 99.9%
225 2
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
225 2
 
< 0.1%
359 601448
> 99.9%
ValueCountFrequency (%)
359 601448
> 99.9%
225 2
 
< 0.1%

orderKey
Real number (ℝ)

Distinct29
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1103.758884
Minimum731
Maximum1494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.375082image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum731
5-th percentile732
Q1734
median1452
Q31459
95-th percentile1459
Maximum1494
Range763
Interquartile range (IQR)725

Descriptive statistics

Standard deviation356.5628898
Coefficient of variation (CV)0.3230441857
Kurtosis-1.989982754
Mean1103.758884
Median Absolute Deviation (MAD)42
Skewness-0.01248992439
Sum663853573
Variance127137.0944
MonotonicityNot monotonic
2025-01-07T10:47:23.432086image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1459 297636
49.5%
734 129084
21.5%
733 47588
 
7.9%
732 47294
 
7.9%
803 30383
 
5.1%
785 11977
 
2.0%
731 11375
 
1.9%
798 10781
 
1.8%
783 5645
 
0.9%
1452 1652
 
0.3%
Other values (19) 8033
 
1.3%
ValueCountFrequency (%)
731 11375
 
1.9%
732 47294
 
7.9%
733 47588
 
7.9%
734 129084
21.5%
735 419
 
0.1%
ValueCountFrequency (%)
1494 729
 
0.1%
1459 297636
49.5%
1454 3
 
< 0.1%
1453 1385
 
0.2%
1452 1652
 
0.3%

familyKey
Real number (ℝ)

Distinct158
Distinct (%)< 0.1%
Missing1158
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean705985.534
Minimum2665
Maximum10678631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.497990image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2665
5-th percentile5313
Q15510
median9366
Q39679
95-th percentile3240723
Maximum10678631
Range10675966
Interquartile range (IQR)4169

Descriptive statistics

Standard deviation1406293.563
Coefficient of variation (CV)1.991958043
Kurtosis2.866452768
Mean705985.534
Median Absolute Deviation (MAD)3856
Skewness1.820345281
Sum4.237981742 × 1011
Variance1.977661584 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:23.567994image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3240723 107243
17.8%
5510 93911
15.6%
9366 55530
 
9.2%
9456 46130
 
7.7%
5534 27470
 
4.6%
5314 23642
 
3.9%
9368 22260
 
3.7%
5504 19997
 
3.3%
5719 13560
 
2.3%
9701 12559
 
2.1%
Other values (148) 177991
29.6%
ValueCountFrequency (%)
2665 2
 
< 0.1%
5297 59
 
< 0.1%
5298 4288
0.7%
5299 48
 
< 0.1%
5300 73
 
< 0.1%
ValueCountFrequency (%)
10678631 132
 
< 0.1%
7872440 1
 
< 0.1%
7456382 3490
0.6%
4828821 1
 
< 0.1%
4827490 25
 
< 0.1%

genusKey
Real number (ℝ)

Distinct1129
Distinct (%)0.2%
Missing1999
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean2914748.82
Minimum2301996
Maximum10943840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.633747image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2301996
5-th percentile2432752
Q12435239
median2437961
Q32439552
95-th percentile5219857
Maximum10943840
Range8641844
Interquartile range (IQR)4313

Descriptive statistics

Standard deviation1423876.922
Coefficient of variation (CV)0.4885075902
Kurtosis11.86162539
Mean2914748.82
Median Absolute Deviation (MAD)2103
Skewness3.432019278
Sum1.74725201 × 1012
Variance2.027425489 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:23.695862image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2437961 38753
 
6.4%
2438591 19877
 
3.3%
2439223 16463
 
2.7%
2435935 15826
 
2.6%
2433258 12467
 
2.1%
2433174 12281
 
2.0%
2440446 11894
 
2.0%
2437422 11871
 
2.0%
2438904 11447
 
1.9%
9800657 10554
 
1.8%
Other values (1119) 438019
72.8%
ValueCountFrequency (%)
2301996 2
 
< 0.1%
2311276 121
< 0.1%
2432086 102
< 0.1%
2432089 36
 
< 0.1%
2432110 8
 
< 0.1%
ValueCountFrequency (%)
10943840 480
 
0.1%
10832425 90
 
< 0.1%
9800657 10554
1.8%
9553756 15
 
< 0.1%
9531221 887
 
0.1%

subgenusKey
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

speciesKey
Real number (ℝ)

Missing 

Distinct3897
Distinct (%)0.7%
Missing29663
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean3491921.611
Minimum2432087
Maximum12178528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:23.759865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2432087
5-th percentile2433011
Q12436886
median2438800
Q35218556
95-th percentile7838352
Maximum12178528
Range9746441
Interquartile range (IQR)2781670

Descriptive statistics

Standard deviation1873847.814
Coefficient of variation (CV)0.5366236767
Kurtosis2.586411263
Mean3491921.611
Median Absolute Deviation (MAD)2781
Skewness1.783626314
Sum1.996638874 × 1012
Variance3.51130563 × 1012
MonotonicityNot monotonic
2025-01-07T10:47:23.826451image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2437967 15647
 
2.6%
2440447 11869
 
2.0%
2433176 8329
 
1.4%
2438019 7347
 
1.2%
2438655 6840
 
1.1%
7429082 6399
 
1.1%
2433272 5482
 
0.9%
2439270 5412
 
0.9%
5219153 4558
 
0.8%
5706760 4437
 
0.7%
Other values (3887) 495468
82.4%
(Missing) 29663
 
4.9%
ValueCountFrequency (%)
2432087 102
< 0.1%
2432111 1
 
< 0.1%
2432112 7
 
< 0.1%
2432119 46
< 0.1%
2432120 2
 
< 0.1%
ValueCountFrequency (%)
12178528 5
 
< 0.1%
11839479 56
< 0.1%
11804100 24
 
< 0.1%
11693419 4
 
< 0.1%
11577247 134
< 0.1%

species
Text

Missing 

Distinct3897
Distinct (%)0.7%
Missing29663
Missing (%)4.9%
Memory size4.6 MiB
2025-01-07T10:47:24.007956image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length26
Mean length18.14441541
Min length8

Characters and Unicode

Total characters10374759
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique406 ?
Unique (%)0.1%

Sample

1st rowPotos flavus
2nd rowMicrotus longicaudus
3rd rowCarollia brevicaudum
4th rowPeromyscus mexicanus
5th rowTursiops truncatus
ValueCountFrequency (%)
peromyscus 38710
 
3.4%
rattus 21793
 
1.9%
microtus 19863
 
1.7%
sorex 15805
 
1.4%
maniculatus 15647
 
1.4%
artibeus 12162
 
1.1%
tursiops 11892
 
1.0%
truncatus 11873
 
1.0%
tamias 11870
 
1.0%
carollia 11315
 
1.0%
Other values (3847) 972646
85.1%
2025-01-07T10:47:24.267478image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1138591
 
11.0%
i 850505
 
8.2%
a 832841
 
8.0%
u 789136
 
7.6%
o 733517
 
7.1%
r 656869
 
6.3%
e 630821
 
6.1%
571788
 
5.5%
t 508552
 
4.9%
l 479658
 
4.6%
Other values (41) 3182481
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10374759
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1138591
 
11.0%
i 850505
 
8.2%
a 832841
 
8.0%
u 789136
 
7.6%
o 733517
 
7.1%
r 656869
 
6.3%
e 630821
 
6.1%
571788
 
5.5%
t 508552
 
4.9%
l 479658
 
4.6%
Other values (41) 3182481
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10374759
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1138591
 
11.0%
i 850505
 
8.2%
a 832841
 
8.0%
u 789136
 
7.6%
o 733517
 
7.1%
r 656869
 
6.3%
e 630821
 
6.1%
571788
 
5.5%
t 508552
 
4.9%
l 479658
 
4.6%
Other values (41) 3182481
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10374759
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1138591
 
11.0%
i 850505
 
8.2%
a 832841
 
8.0%
u 789136
 
7.6%
o 733517
 
7.1%
r 656869
 
6.3%
e 630821
 
6.1%
571788
 
5.5%
t 508552
 
4.9%
l 479658
 
4.6%
Other values (41) 3182481
30.7%
Distinct6815
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:24.478627image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length147
Median length76
Mean length34.65024416
Min length7

Characters and Unicode

Total characters20840424
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique793 ?
Unique (%)0.1%

Sample

1st rowPotos flavus (Schreber, 1774)
2nd rowMicrotus longicaudus (Merriam, 1888)
3rd rowCarollia brevicaudum (Schinz, 1821)
4th rowPeromyscus mexicanus (Saussure, 1860)
5th rowTursiops truncatus (Montagu, 1821)
ValueCountFrequency (%)
linnaeus 54248
 
2.2%
1758 48971
 
2.0%
thomas 43832
 
1.8%
peromyscus 38753
 
1.6%
merriam 31855
 
1.3%
24205
 
1.0%
1821 22026
 
0.9%
rattus 21929
 
0.9%
wagner 21848
 
0.9%
j.a.allen 20548
 
0.8%
Other values (6260) 2160706
86.8%
2025-01-07T10:47:24.768613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1887470
 
9.1%
s 1613579
 
7.7%
a 1375849
 
6.6%
i 1277042
 
6.1%
e 1193882
 
5.7%
r 1077033
 
5.2%
u 1043189
 
5.0%
o 1026603
 
4.9%
n 888434
 
4.3%
l 794841
 
3.8%
Other values (70) 8662502
41.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20840424
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1887470
 
9.1%
s 1613579
 
7.7%
a 1375849
 
6.6%
i 1277042
 
6.1%
e 1193882
 
5.7%
r 1077033
 
5.2%
u 1043189
 
5.0%
o 1026603
 
4.9%
n 888434
 
4.3%
l 794841
 
3.8%
Other values (70) 8662502
41.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20840424
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1887470
 
9.1%
s 1613579
 
7.7%
a 1375849
 
6.6%
i 1277042
 
6.1%
e 1193882
 
5.7%
r 1077033
 
5.2%
u 1043189
 
5.0%
o 1026603
 
4.9%
n 888434
 
4.3%
l 794841
 
3.8%
Other values (70) 8662502
41.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20840424
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1887470
 
9.1%
s 1613579
 
7.7%
a 1375849
 
6.6%
i 1277042
 
6.1%
e 1193882
 
5.7%
r 1077033
 
5.2%
u 1043189
 
5.0%
o 1026603
 
4.9%
n 888434
 
4.3%
l 794841
 
3.8%
Other values (70) 8662502
41.6%
Distinct7805
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:24.953509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length43
Mean length22.61255364
Min length5

Characters and Unicode

Total characters13600343
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique898 ?
Unique (%)0.1%

Sample

1st rowPotos flavus
2nd rowMicrotus longicaudus longicaudus
3rd rowCarollia brevicauda
4th rowPeromyscus mexicanus totontepecus
5th rowTursiops truncatus
ValueCountFrequency (%)
peromyscus 38753
 
2.6%
sp 28343
 
1.9%
rattus 21929
 
1.5%
microtus 19877
 
1.3%
maniculatus 15880
 
1.1%
sorex 15831
 
1.1%
artibeus 12470
 
0.8%
carollia 12281
 
0.8%
tursiops 11895
 
0.8%
truncatus 11875
 
0.8%
Other values (5505) 1302266
87.3%
2025-01-07T10:47:25.203675image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13600343
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1517215
 
11.2%
i 1187099
 
8.7%
a 1082276
 
8.0%
u 980723
 
7.2%
o 902387
 
6.6%
889949
 
6.5%
e 862255
 
6.3%
r 848292
 
6.2%
n 665623
 
4.9%
l 634731
 
4.7%
Other values (53) 4029793
29.6%

typifiedName
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

protocol
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:25.256676image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1804353
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 601451
100.0%
2025-01-07T10:47:25.350048image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 601451
33.3%
M 601451
33.3%
L 601451
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1804353
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 601451
33.3%
M 601451
33.3%
L 601451
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1804353
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 601451
33.3%
M 601451
33.3%
L 601451
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1804353
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 601451
33.3%
M 601451
33.3%
L 601451
33.3%
Distinct185984
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:25.501908image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99573698
Min length20

Characters and Unicode

Total characters14432260
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38937 ?
Unique (%)6.5%

Sample

1st row2024-12-02T13:58:01.255Z
2nd row2024-12-02T13:59:38.442Z
3rd row2024-12-02T13:56:07.605Z
4th row2024-12-02T13:58:24.850Z
5th row2024-12-02T13:56:12.476Z
ValueCountFrequency (%)
2024-12-02t13:57:24.313z 17
 
< 0.1%
2024-12-02t13:57:59.063z 17
 
< 0.1%
2024-12-02t13:57:52.813z 17
 
< 0.1%
2024-12-02t13:57:14.377z 17
 
< 0.1%
2024-12-02t13:57:15.231z 17
 
< 0.1%
2024-12-02t13:57:52.024z 16
 
< 0.1%
2024-12-02t13:57:50.062z 16
 
< 0.1%
2024-12-02t13:57:25.776z 16
 
< 0.1%
2024-12-02t13:56:59.760z 15
 
< 0.1%
2024-12-02t13:57:42.979z 15
 
< 0.1%
Other values (185974) 601288
> 99.9%
2025-01-07T10:47:25.735866image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14432260
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2746380
19.0%
0 1525337
10.6%
1 1517832
10.5%
- 1202902
8.3%
: 1202902
8.3%
4 967155
 
6.7%
5 955236
 
6.6%
3 952306
 
6.6%
T 601451
 
4.2%
Z 601451
 
4.2%
Other values (5) 2159308
15.0%

lastCrawled
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:25.800375image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters14434824
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-02T11:48:23.416Z
2nd row2024-12-02T11:48:23.416Z
3rd row2024-12-02T11:48:23.416Z
4th row2024-12-02T11:48:23.416Z
5th row2024-12-02T11:48:23.416Z
ValueCountFrequency (%)
2024-12-02t11:48:23.416z 601451
100.0%
2025-01-07T10:47:25.907312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3007255
20.8%
1 2405804
16.7%
4 1804353
12.5%
0 1202902
 
8.3%
- 1202902
 
8.3%
: 1202902
 
8.3%
T 601451
 
4.2%
8 601451
 
4.2%
3 601451
 
4.2%
. 601451
 
4.2%
Other values (2) 1202902
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14434824
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3007255
20.8%
1 2405804
16.7%
4 1804353
12.5%
0 1202902
 
8.3%
- 1202902
 
8.3%
: 1202902
 
8.3%
T 601451
 
4.2%
8 601451
 
4.2%
3 601451
 
4.2%
. 601451
 
4.2%
Other values (2) 1202902
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14434824
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3007255
20.8%
1 2405804
16.7%
4 1804353
12.5%
0 1202902
 
8.3%
- 1202902
 
8.3%
: 1202902
 
8.3%
T 601451
 
4.2%
8 601451
 
4.2%
3 601451
 
4.2%
. 601451
 
4.2%
Other values (2) 1202902
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14434824
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3007255
20.8%
1 2405804
16.7%
4 1804353
12.5%
0 1202902
 
8.3%
- 1202902
 
8.3%
: 1202902
 
8.3%
T 601451
 
4.2%
8 601451
 
4.2%
3 601451
 
4.2%
. 601451
 
4.2%
Other values (2) 1202902
 
8.3%
Distinct2
Distinct (%)< 0.1%
Missing2505
Missing (%)0.4%
Memory size4.6 MiB
True
372656 
False
226290 
(Missing)
 
2505
ValueCountFrequency (%)
True 372656
62.0%
False 226290
37.6%
(Missing) 2505
 
0.4%
2025-01-07T10:47:26.038888image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

relativeOrganismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

projectId
Unsupported

Missing  Rejected  Unsupported 

Missing601451
Missing (%)100.0%
Memory size4.6 MiB

isSequenced
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size587.5 KiB
False
600397 
True
 
1054
ValueCountFrequency (%)
False 600397
99.8%
True 1054
 
0.2%
2025-01-07T10:47:26.076983image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

gbifRegion
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing15955
Missing (%)2.7%
Memory size4.6 MiB
2025-01-07T10:47:26.113269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.49816395
Min length4

Characters and Unicode

Total characters6146633
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLATIN_AMERICA
2nd rowNORTH_AMERICA
3rd rowLATIN_AMERICA
4th rowLATIN_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 245840
42.0%
latin_america 145714
24.9%
africa 101325
17.3%
asia 63583
 
10.9%
europe 17807
 
3.0%
oceania 8321
 
1.4%
antarctica 2906
 
0.5%
2025-01-07T10:47:26.213274image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1283998
20.9%
R 759432
12.4%
I 713403
11.6%
C 507012
 
8.2%
E 435489
 
7.1%
N 402781
 
6.6%
T 397366
 
6.5%
M 391554
 
6.4%
_ 391554
 
6.4%
O 271968
 
4.4%
Other values (6) 592076
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6146633
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1283998
20.9%
R 759432
12.4%
I 713403
11.6%
C 507012
 
8.2%
E 435489
 
7.1%
N 402781
 
6.6%
T 397366
 
6.5%
M 391554
 
6.4%
_ 391554
 
6.4%
O 271968
 
4.4%
Other values (6) 592076
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6146633
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1283998
20.9%
R 759432
12.4%
I 713403
11.6%
C 507012
 
8.2%
E 435489
 
7.1%
N 402781
 
6.6%
T 397366
 
6.5%
M 391554
 
6.4%
_ 391554
 
6.4%
O 271968
 
4.4%
Other values (6) 592076
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6146633
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1283998
20.9%
R 759432
12.4%
I 713403
11.6%
C 507012
 
8.2%
E 435489
 
7.1%
N 402781
 
6.6%
T 397366
 
6.5%
M 391554
 
6.4%
_ 391554
 
6.4%
O 271968
 
4.4%
Other values (6) 592076
9.6%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-01-07T10:47:26.261275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters7818863
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 601451
100.0%
2025-01-07T10:47:26.359116image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1202902
15.4%
A 1202902
15.4%
N 601451
7.7%
O 601451
7.7%
T 601451
7.7%
H 601451
7.7%
_ 601451
7.7%
M 601451
7.7%
E 601451
7.7%
I 601451
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7818863
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1202902
15.4%
A 1202902
15.4%
N 601451
7.7%
O 601451
7.7%
T 601451
7.7%
H 601451
7.7%
_ 601451
7.7%
M 601451
7.7%
E 601451
7.7%
I 601451
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7818863
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1202902
15.4%
A 1202902
15.4%
N 601451
7.7%
O 601451
7.7%
T 601451
7.7%
H 601451
7.7%
_ 601451
7.7%
M 601451
7.7%
E 601451
7.7%
I 601451
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7818863
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1202902
15.4%
A 1202902
15.4%
N 601451
7.7%
O 601451
7.7%
T 601451
7.7%
H 601451
7.7%
_ 601451
7.7%
M 601451
7.7%
E 601451
7.7%
I 601451
7.7%

level0Gid
Text

Missing 

Distinct157
Distinct (%)0.1%
Missing473902
Missing (%)78.8%
Memory size4.6 MiB
2025-01-07T10:47:26.485718image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters382647
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowVEN
2nd rowAFG
3rd rowZ01
4th rowVEN
5th rowZAF
ValueCountFrequency (%)
ven 22481
17.6%
usa 11290
 
8.9%
zaf 9365
 
7.3%
gha 6969
 
5.5%
mar 6781
 
5.3%
idn 6468
 
5.1%
bwa 4488
 
3.5%
bfa 4128
 
3.2%
moz 3329
 
2.6%
pan 3025
 
2.4%
Other values (147) 49225
38.6%
2025-01-07T10:47:26.669311image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 57657
15.1%
N 44072
 
11.5%
E 35574
 
9.3%
V 25784
 
6.7%
M 21228
 
5.5%
S 19507
 
5.1%
Z 16511
 
4.3%
G 16274
 
4.3%
F 15976
 
4.2%
B 15801
 
4.1%
Other values (19) 114263
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 382647
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 57657
15.1%
N 44072
 
11.5%
E 35574
 
9.3%
V 25784
 
6.7%
M 21228
 
5.5%
S 19507
 
5.1%
Z 16511
 
4.3%
G 16274
 
4.3%
F 15976
 
4.2%
B 15801
 
4.1%
Other values (19) 114263
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 382647
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 57657
15.1%
N 44072
 
11.5%
E 35574
 
9.3%
V 25784
 
6.7%
M 21228
 
5.5%
S 19507
 
5.1%
Z 16511
 
4.3%
G 16274
 
4.3%
F 15976
 
4.2%
B 15801
 
4.1%
Other values (19) 114263
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 382647
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 57657
15.1%
N 44072
 
11.5%
E 35574
 
9.3%
V 25784
 
6.7%
M 21228
 
5.5%
S 19507
 
5.1%
Z 16511
 
4.3%
G 16274
 
4.3%
F 15976
 
4.2%
B 15801
 
4.1%
Other values (19) 114263
29.9%

level0Name
Text

Missing 

Distinct157
Distinct (%)0.1%
Missing473902
Missing (%)78.8%
Memory size4.6 MiB
2025-01-07T10:47:26.835801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length24
Mean length9.472931971
Min length4

Characters and Unicode

Total characters1208263
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowVenezuela
2nd rowAfghanistan
3rd rowJammu and Kashmir
4th rowVenezuela
5th rowSouth Africa
ValueCountFrequency (%)
venezuela 22481
 
13.1%
united 11945
 
7.0%
states 11376
 
6.6%
south 10173
 
5.9%
africa 9365
 
5.5%
ghana 6969
 
4.1%
morocco 6781
 
3.9%
indonesia 6468
 
3.8%
botswana 4488
 
2.6%
burkina 4128
 
2.4%
Other values (185) 77505
45.1%
2025-01-07T10:47:27.070251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 157852
 
13.1%
e 138859
 
11.5%
n 95632
 
7.9%
i 91451
 
7.6%
o 66935
 
5.5%
t 62305
 
5.2%
u 52405
 
4.3%
r 46349
 
3.8%
44130
 
3.7%
l 37921
 
3.1%
Other values (49) 414424
34.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1208263
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 157852
 
13.1%
e 138859
 
11.5%
n 95632
 
7.9%
i 91451
 
7.6%
o 66935
 
5.5%
t 62305
 
5.2%
u 52405
 
4.3%
r 46349
 
3.8%
44130
 
3.7%
l 37921
 
3.1%
Other values (49) 414424
34.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1208263
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 157852
 
13.1%
e 138859
 
11.5%
n 95632
 
7.9%
i 91451
 
7.6%
o 66935
 
5.5%
t 62305
 
5.2%
u 52405
 
4.3%
r 46349
 
3.8%
44130
 
3.7%
l 37921
 
3.1%
Other values (49) 414424
34.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1208263
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 157852
 
13.1%
e 138859
 
11.5%
n 95632
 
7.9%
i 91451
 
7.6%
o 66935
 
5.5%
t 62305
 
5.2%
u 52405
 
4.3%
r 46349
 
3.8%
44130
 
3.7%
l 37921
 
3.1%
Other values (49) 414424
34.3%

level1Gid
Text

Missing 

Distinct906
Distinct (%)0.7%
Missing473930
Missing (%)78.8%
Memory size4.6 MiB
2025-01-07T10:47:27.285428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.41927212
Min length6

Characters and Unicode

Total characters946113
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)0.1%

Sample

1st rowVEN.6_1
2nd rowAFG.15_1
3rd rowZ01.14_1
4th rowVEN.1_1
5th rowZAF.8_1
ValueCountFrequency (%)
ven.1_1 6194
 
4.9%
zaf.8_1 3031
 
2.4%
ven.6_1 2186
 
1.7%
bwa.12_1 2159
 
1.7%
ven.12_1 1504
 
1.2%
caf.16_1 1500
 
1.2%
eth.8_1 1491
 
1.2%
mar.6_1 1470
 
1.2%
ven.24_1 1465
 
1.1%
mar.12_1 1449
 
1.1%
Other values (896) 105072
82.4%
2025-01-07T10:47:27.575133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 179942
19.0%
_ 127518
13.5%
. 120552
12.7%
A 57624
 
6.1%
N 44072
 
4.7%
2 40011
 
4.2%
E 35574
 
3.8%
V 25784
 
2.7%
M 21227
 
2.2%
4 20211
 
2.1%
Other values (28) 273598
28.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 946113
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 179942
19.0%
_ 127518
13.5%
. 120552
12.7%
A 57624
 
6.1%
N 44072
 
4.7%
2 40011
 
4.2%
E 35574
 
3.8%
V 25784
 
2.7%
M 21227
 
2.2%
4 20211
 
2.1%
Other values (28) 273598
28.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 946113
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 179942
19.0%
_ 127518
13.5%
. 120552
12.7%
A 57624
 
6.1%
N 44072
 
4.7%
2 40011
 
4.2%
E 35574
 
3.8%
V 25784
 
2.7%
M 21227
 
2.2%
4 20211
 
2.1%
Other values (28) 273598
28.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 946113
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 179942
19.0%
_ 127518
13.5%
. 120552
12.7%
A 57624
 
6.1%
N 44072
 
4.7%
2 40011
 
4.2%
E 35574
 
3.8%
V 25784
 
2.7%
M 21227
 
2.2%
4 20211
 
2.1%
Other values (28) 273598
28.9%

level1Name
Text

Missing 

Distinct882
Distinct (%)0.7%
Missing473930
Missing (%)78.8%
Memory size4.6 MiB
2025-01-07T10:47:27.758777image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length9.408136699
Min length3

Characters and Unicode

Total characters1199735
Distinct characters90
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)0.1%

Sample

1st rowBolívar
2nd rowKandahar
3rd rowJammu and Kashmir
4th rowAmazonas
5th rowNorthern Cape
ValueCountFrequency (%)
8657
 
4.8%
amazonas 6326
 
3.5%
cape 5248
 
2.9%
northern 4629
 
2.6%
eastern 4155
 
2.3%
bolívar 2189
 
1.2%
north-west 2159
 
1.2%
barat 2126
 
1.2%
west 1913
 
1.1%
western 1800
 
1.0%
Other values (1015) 140238
78.2%
2025-01-07T10:47:28.004226image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 186875
15.6%
r 89084
 
7.4%
n 79844
 
6.7%
e 79607
 
6.6%
o 67186
 
5.6%
t 58756
 
4.9%
i 53839
 
4.5%
s 53114
 
4.4%
51919
 
4.3%
l 43110
 
3.6%
Other values (80) 436401
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1199735
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 186875
15.6%
r 89084
 
7.4%
n 79844
 
6.7%
e 79607
 
6.6%
o 67186
 
5.6%
t 58756
 
4.9%
i 53839
 
4.5%
s 53114
 
4.4%
51919
 
4.3%
l 43110
 
3.6%
Other values (80) 436401
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1199735
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 186875
15.6%
r 89084
 
7.4%
n 79844
 
6.7%
e 79607
 
6.6%
o 67186
 
5.6%
t 58756
 
4.9%
i 53839
 
4.5%
s 53114
 
4.4%
51919
 
4.3%
l 43110
 
3.6%
Other values (80) 436401
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1199735
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 186875
15.6%
r 89084
 
7.4%
n 79844
 
6.7%
e 79607
 
6.6%
o 67186
 
5.6%
t 58756
 
4.9%
i 53839
 
4.5%
s 53114
 
4.4%
51919
 
4.3%
l 43110
 
3.6%
Other values (80) 436401
36.4%

level2Gid
Text

Missing 

Distinct2378
Distinct (%)1.9%
Missing475037
Missing (%)79.0%
Memory size4.6 MiB
2025-01-07T10:47:28.226907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.659871533
Min length7

Characters and Unicode

Total characters1221143
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique658 ?
Unique (%)0.5%

Sample

1st rowVEN.6.10_1
2nd rowAFG.15.3_1
3rd rowZ01.14.3_1
4th rowVEN.1.6_1
5th rowZAF.8.5_1
ValueCountFrequency (%)
ven.1.5_1 2542
 
2.0%
bwa.12.2_1 1980
 
1.6%
ven.1.1_1 1644
 
1.3%
caf.16.2_1 1500
 
1.2%
eth.8.8_1 1196
 
0.9%
zaf.8.5_1 1077
 
0.9%
ven.6.10_1 1052
 
0.8%
sle.2.1_1 1049
 
0.8%
sle.1.2_1 1037
 
0.8%
zaf.8.4_1 1035
 
0.8%
Other values (2368) 112302
88.8%
2025-01-07T10:47:28.500149image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 245856
20.1%
1 216878
17.8%
_ 126414
 
10.4%
2 73592
 
6.0%
A 57593
 
4.7%
N 44067
 
3.6%
E 35567
 
2.9%
4 35248
 
2.9%
3 33422
 
2.7%
5 26946
 
2.2%
Other values (28) 325560
26.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1221143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 245856
20.1%
1 216878
17.8%
_ 126414
 
10.4%
2 73592
 
6.0%
A 57593
 
4.7%
N 44067
 
3.6%
E 35567
 
2.9%
4 35248
 
2.9%
3 33422
 
2.7%
5 26946
 
2.2%
Other values (28) 325560
26.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1221143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 245856
20.1%
1 216878
17.8%
_ 126414
 
10.4%
2 73592
 
6.0%
A 57593
 
4.7%
N 44067
 
3.6%
E 35567
 
2.9%
4 35248
 
2.9%
3 33422
 
2.7%
5 26946
 
2.2%
Other values (28) 325560
26.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1221143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 245856
20.1%
1 216878
17.8%
_ 126414
 
10.4%
2 73592
 
6.0%
A 57593
 
4.7%
N 44067
 
3.6%
E 35567
 
2.9%
4 35248
 
2.9%
3 33422
 
2.7%
5 26946
 
2.2%
Other values (28) 325560
26.7%

level2Name
Text

Missing 

Distinct2276
Distinct (%)1.8%
Missing475037
Missing (%)79.0%
Memory size4.6 MiB
2025-01-07T10:47:28.705621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length27
Mean length8.596326356
Min length2

Characters and Unicode

Total characters1086696
Distinct characters121
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique606 ?
Unique (%)0.5%

Sample

1st rowSifontes
2nd rowDaman
3rd rowBandipore
4th rowMaroa
5th rowSiyanda
ValueCountFrequency (%)
west 3557
 
2.1%
manapiare 2542
 
1.5%
ngamiland 2159
 
1.3%
south 2001
 
1.2%
alto 1647
 
1.0%
orinoco 1644
 
1.0%
east 1641
 
1.0%
nola 1500
 
0.9%
bolívar 1475
 
0.9%
miranda 1344
 
0.8%
Other values (2539) 146175
88.2%
2025-01-07T10:47:28.972357image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 156174
 
14.4%
o 74427
 
6.8%
n 72702
 
6.7%
e 72325
 
6.7%
i 68255
 
6.3%
r 58313
 
5.4%
t 45881
 
4.2%
u 41995
 
3.9%
39271
 
3.6%
l 37304
 
3.4%
Other values (111) 420049
38.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1086696
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 156174
 
14.4%
o 74427
 
6.8%
n 72702
 
6.7%
e 72325
 
6.7%
i 68255
 
6.3%
r 58313
 
5.4%
t 45881
 
4.2%
u 41995
 
3.9%
39271
 
3.6%
l 37304
 
3.4%
Other values (111) 420049
38.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1086696
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 156174
 
14.4%
o 74427
 
6.8%
n 72702
 
6.7%
e 72325
 
6.7%
i 68255
 
6.3%
r 58313
 
5.4%
t 45881
 
4.2%
u 41995
 
3.9%
39271
 
3.6%
l 37304
 
3.4%
Other values (111) 420049
38.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1086696
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 156174
 
14.4%
o 74427
 
6.8%
n 72702
 
6.7%
e 72325
 
6.7%
i 68255
 
6.3%
r 58313
 
5.4%
t 45881
 
4.2%
u 41995
 
3.9%
39271
 
3.6%
l 37304
 
3.4%
Other values (111) 420049
38.7%

level3Gid
Text

Missing 

Distinct1589
Distinct (%)2.6%
Missing539154
Missing (%)89.6%
Memory size4.6 MiB
2025-01-07T10:47:29.182798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.6395011
Min length11

Characters and Unicode

Total characters725106
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique471 ?
Unique (%)0.8%

Sample

1st rowZ01.14.3.1_1
2nd rowZAF.8.5.3_1
3rd rowZ06.6.1.4_1
4th rowBFA.8.2.6_1
5th rowPHL.59.10.11_1
ValueCountFrequency (%)
sle.1.2.8_1 1037
 
1.7%
eth.8.8.11_1 988
 
1.6%
pan.11.1.1_1 727
 
1.2%
sle.2.1.13_1 717
 
1.2%
mar.6.2.2_1 637
 
1.0%
pan.2.10.3_1 610
 
1.0%
ssd.1.2.1_1 426
 
0.7%
zaf.8.5.3_1 419
 
0.7%
ben.2.5.2_1 418
 
0.7%
pan.4.2.6_1 413
 
0.7%
Other values (1579) 55905
89.7%
2025-01-07T10:47:29.460567image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 186891
25.8%
1 125870
17.4%
_ 62297
 
8.6%
2 41681
 
5.7%
3 25313
 
3.5%
A 25141
 
3.5%
4 22242
 
3.1%
5 18614
 
2.6%
6 15803
 
2.2%
Z 15767
 
2.2%
Other values (24) 185487
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 725106
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 186891
25.8%
1 125870
17.4%
_ 62297
 
8.6%
2 41681
 
5.7%
3 25313
 
3.5%
A 25141
 
3.5%
4 22242
 
3.1%
5 18614
 
2.6%
6 15803
 
2.2%
Z 15767
 
2.2%
Other values (24) 185487
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 725106
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 186891
25.8%
1 125870
17.4%
_ 62297
 
8.6%
2 41681
 
5.7%
3 25313
 
3.5%
A 25141
 
3.5%
4 22242
 
3.1%
5 18614
 
2.6%
6 15803
 
2.2%
Z 15767
 
2.2%
Other values (24) 185487
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 725106
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 186891
25.8%
1 125870
17.4%
_ 62297
 
8.6%
2 41681
 
5.7%
3 25313
 
3.5%
A 25141
 
3.5%
4 22242
 
3.1%
5 18614
 
2.6%
6 15803
 
2.2%
Z 15767
 
2.2%
Other values (24) 185487
25.6%

level3Name
Text

Missing 

Distinct1550
Distinct (%)2.5%
Missing539390
Missing (%)89.7%
Memory size4.6 MiB
2025-01-07T10:47:29.672097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length27
Mean length9.01318058
Min length2

Characters and Unicode

Total characters559367
Distinct characters107
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique451 ?
Unique (%)0.7%

Sample

1st rown.a. ( 4)
2nd rowKai !Garib
3rd rowKargil
4th rowYamba
5th rowMalaking Patag
ValueCountFrequency (%)
ward 1627
 
1.9%
n.a 1294
 
1.5%
1255
 
1.5%
lower 1037
 
1.2%
bambara 1037
 
1.2%
seka 993
 
1.1%
chekorsa 988
 
1.1%
na 839
 
1.0%
arraiján 727
 
0.8%
tambakha 717
 
0.8%
Other values (1794) 75841
87.8%
2025-01-07T10:47:29.948266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 81980
 
14.7%
i 36730
 
6.6%
n 36575
 
6.5%
o 35678
 
6.4%
e 34413
 
6.2%
r 27496
 
4.9%
u 26462
 
4.7%
24294
 
4.3%
g 17364
 
3.1%
l 17126
 
3.1%
Other values (97) 221249
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 559367
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 81980
 
14.7%
i 36730
 
6.6%
n 36575
 
6.5%
o 35678
 
6.4%
e 34413
 
6.2%
r 27496
 
4.9%
u 26462
 
4.7%
24294
 
4.3%
g 17364
 
3.1%
l 17126
 
3.1%
Other values (97) 221249
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 559367
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 81980
 
14.7%
i 36730
 
6.6%
n 36575
 
6.5%
o 35678
 
6.4%
e 34413
 
6.2%
r 27496
 
4.9%
u 26462
 
4.7%
24294
 
4.3%
g 17364
 
3.1%
l 17126
 
3.1%
Other values (97) 221249
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 559367
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 81980
 
14.7%
i 36730
 
6.6%
n 36575
 
6.5%
o 35678
 
6.4%
e 34413
 
6.2%
r 27496
 
4.9%
u 26462
 
4.7%
24294
 
4.3%
g 17364
 
3.1%
l 17126
 
3.1%
Other values (97) 221249
39.6%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing210302
Missing (%)35.0%
Memory size4.6 MiB
2025-01-07T10:47:30.006647image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters782298
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLC
2nd rowLC
3rd rowLC
4th rowLC
5th rowLC
ValueCountFrequency (%)
lc 316013
80.8%
ne 32299
 
8.3%
vu 20062
 
5.1%
nt 8397
 
2.1%
en 8040
 
2.1%
dd 3578
 
0.9%
cr 2355
 
0.6%
ex 375
 
0.1%
ew 30
 
< 0.1%
2025-01-07T10:47:30.101588image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 318368
40.7%
L 316013
40.4%
N 48736
 
6.2%
E 40744
 
5.2%
V 20062
 
2.6%
U 20062
 
2.6%
T 8397
 
1.1%
D 7156
 
0.9%
R 2355
 
0.3%
X 375
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 782298
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 318368
40.7%
L 316013
40.4%
N 48736
 
6.2%
E 40744
 
5.2%
V 20062
 
2.6%
U 20062
 
2.6%
T 8397
 
1.1%
D 7156
 
0.9%
R 2355
 
0.3%
X 375
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 782298
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 318368
40.7%
L 316013
40.4%
N 48736
 
6.2%
E 40744
 
5.2%
V 20062
 
2.6%
U 20062
 
2.6%
T 8397
 
1.1%
D 7156
 
0.9%
R 2355
 
0.3%
X 375
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 782298
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 318368
40.7%
L 316013
40.4%
N 48736
 
6.2%
E 40744
 
5.2%
V 20062
 
2.6%
U 20062
 
2.6%
T 8397
 
1.1%
D 7156
 
0.9%
R 2355
 
0.3%
X 375
 
< 0.1%